Convolutional Neural Networks

Project: Write an Algorithm for a Dog Identification App


In this notebook, some template code has already been provided for you, and you will need to implement additional functionality to successfully complete this project. You will not need to modify the included code beyond what is requested. Sections that begin with '(IMPLEMENTATION)' in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section, and the specifics of the implementation are marked in the code block with a 'TODO' statement. Please be sure to read the instructions carefully!

Note: Once you have completed all of the code implementations, you need to finalize your work by exporting the iPython Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to \n", "File -> Download as -> HTML (.html). Include the finished document along with this notebook as your submission.

In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a 'Question X' header. Carefully read each question and provide thorough answers in the following text boxes that begin with 'Answer:'. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.

Note: Code and Markdown cells can be executed using the Shift + Enter keyboard shortcut. Markdown cells can be edited by double-clicking the cell to enter edit mode.

The rubric contains optional "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. If you decide to pursue the "Stand Out Suggestions", you should include the code in this IPython notebook.


Why We're Here

In this notebook, you will make the first steps towards developing an algorithm that could be used as part of a mobile or web app. At the end of this project, your code will accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling. The image below displays potential sample output of your finished project (... but we expect that each student's algorithm will behave differently!).

Sample Dog Output

In this real-world setting, you will need to piece together a series of models to perform different tasks; for instance, the algorithm that detects humans in an image will be different from the CNN that infers dog breed. There are many points of possible failure, and no perfect algorithm exists. Your imperfect solution will nonetheless create a fun user experience!

The Road Ahead

We break the notebook into separate steps. Feel free to use the links below to navigate the notebook.

  • Step 0: Import Datasets
  • Step 1: Detect Humans
  • Step 2: Detect Dogs
  • Step 3: Create a CNN to Classify Dog Breeds (from Scratch)
  • Step 4: Use a CNN to Classify Dog Breeds (using Transfer Learning)
  • Step 5: Create a CNN to Classify Dog Breeds (using Transfer Learning)
  • Step 6: Write your Algorithm
  • Step 7: Test Your Algorithm

Step 0: Import Datasets

Import Dog Dataset

In the code cell below, we import a dataset of dog images. We populate a few variables through the use of the load_files function from the scikit-learn library:

  • train_files, valid_files, test_files - numpy arrays containing file paths to images
  • train_targets, valid_targets, test_targets - numpy arrays containing onehot-encoded classification labels
  • dog_names - list of string-valued dog breed names for translating labels
In [4]:
from sklearn.datasets import load_files       
from keras.utils import np_utils
import numpy as np
from glob import glob

# define function to load train, test, and validation datasets
def load_dataset(path):
    data = load_files(path)
    dog_files = np.array(data['filenames'])
    dog_targets = np_utils.to_categorical(np.array(data['target']), 133)
    return dog_files, dog_targets

# load train, test, and validation datasets
train_files, train_targets = load_dataset('/data/dog_images/train')
valid_files, valid_targets = load_dataset('/data/dog_images/valid')
test_files, test_targets = load_dataset('/data/dog_images/test')

# load list of dog names
dog_names = [item[20:-1].split('.')[1] for item in sorted(glob("/data/dog_images/train/*/"))]

# print statistics about the dataset
print('There are %d total dog categories.' % len(dog_names))
print('There are %s total dog images.\n' % len(np.hstack([train_files, valid_files, test_files])))
print('There are %d training dog images.' % len(train_files))
print('There are %d validation dog images.' % len(valid_files))
print('There are %d test dog images.'% len(test_files))
Using TensorFlow backend.
There are 133 total dog categories.
There are 8351 total dog images.

There are 6680 training dog images.
There are 835 validation dog images.
There are 836 test dog images.

Import Human Dataset

In the code cell below, we import a dataset of human images, where the file paths are stored in the numpy array human_files.

In [5]:
import random
random.seed(8675309)

# load filenames in shuffled human dataset
human_files = np.array(glob("/data/lfw/*/*"))
random.shuffle(human_files)

# print statistics about the dataset
print('There are %d total human images.' % len(human_files))
There are 13233 total human images.

Step 1: Detect Humans

We use OpenCV's implementation of Haar feature-based cascade classifiers to detect human faces in images. OpenCV provides many pre-trained face detectors, stored as XML files on github. We have downloaded one of these detectors and stored it in the haarcascades directory.

In the next code cell, we demonstrate how to use this detector to find human faces in a sample image.

In [6]:
import cv2                
import matplotlib.pyplot as plt                        
%matplotlib inline                               

def bounding_onhumanface(imgpath):
    # extract pre-trained face detector
    face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_alt.xml')

    # load color (BGR) image
    img = cv2.imread(imgpath)
    # convert BGR image to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # find faces in image
    faces = face_cascade.detectMultiScale(gray)

    # get bounding box for each detected face
    for (x,y,w,h) in faces:
        # add bounding box to color image
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)

    # convert BGR image to RGB for plotting
    cv_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

    # display the image, along with bounding box
    plt.imshow(cv_rgb)
    plt.show()
    # print number of faces detected in the image
    print('Number of faces detected:', len(faces))
    print("*************************")
    
bounding_onhumanface(human_files[5])
Number of faces detected: 1
*************************

Before using any of the face detectors, it is standard procedure to convert the images to grayscale. The detectMultiScale function executes the classifier stored in face_cascade and takes the grayscale image as a parameter.

In the above code, faces is a numpy array of detected faces, where each row corresponds to a detected face. Each detected face is a 1D array with four entries that specifies the bounding box of the detected face. The first two entries in the array (extracted in the above code as x and y) specify the horizontal and vertical positions of the top left corner of the bounding box. The last two entries in the array (extracted here as w and h) specify the width and height of the box.

Write a Human Face Detector

We can use this procedure to write a function that returns True if a human face is detected in an image and False otherwise. This function, aptly named face_detector, takes a string-valued file path to an image as input and appears in the code block below.

In [7]:
# returns "True" if face is detected in image stored at img_path
def humanface_detector(img_path):
    face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_alt.xml')
    img = cv2.imread(img_path)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray)
    return len(faces) > 0

(IMPLEMENTATION) Assess the Human Face Detector

Question 1: Use the code cell below to test the performance of the face_detector function.

  • What percentage of the first 100 images in human_files have a detected human face?
  • What percentage of the first 100 images in dog_files have a detected human face?

Ideally, we would like 100% of human images with a detected face and 0% of dog images with a detected face. You will see that our algorithm falls short of this goal, but still gives acceptable performance. We extract the file paths for the first 100 images from each of the datasets and store them in the numpy arrays human_files_short and dog_files_short.

Answer:

What percentage of the first 100 images in human_files have a detected human face?

The percentage of human faces detected in humanimg are= 100.000%

What percentage of the first 100 images in dog_files have a detected human face?

The percentage of human faces detected in dogimg are= 11.000%

In [5]:
human_files_short = human_files[:100]
dog_files_short = train_files[:100]
# Do NOT modify the code above this line.
import cv2                

print("Testing the performance of the humanface_detector function on the images in human_files_short")
count_humanfaceDetectAlgo_detect_humanface_in_humanimgs=0
for humanimg in human_files_short:
    if(humanface_detector(humanimg)):
        count_humanfaceDetectAlgo_detect_humanface_in_humanimgs += 1
percentage_human_face_detected_in_humanimg=((count_humanfaceDetectAlgo_detect_humanface_in_humanimgs)/len(human_files_short))*100
print("The percentage of human faces detected in humanimg are={0:3.3f}%".format(percentage_human_face_detected_in_humanimg))

print("Testing the performance of the humanface_detector function on the images in dog_files_short")
count_humanfaceDetectAlgo_detect_humanface_in_dogimgs=0
for dogimg in dog_files_short:
    if(humanface_detector(dogimg)):
        count_humanfaceDetectAlgo_detect_humanface_in_dogimgs += 1
percentage_humanface_detected_in_dogimg=((count_humanfaceDetectAlgo_detect_humanface_in_dogimgs)/len(dog_files_short))*100
print("The percentage of human faces detected in dogimg are={0:3.3f}% ".format(percentage_humanface_detected_in_dogimg))
Testing the performance of the humanface_detector function on the images in human_files_short
The percentage of human faces detected in humanimg are=100.000%
Testing the performance of the humanface_detector function on the images in dog_files_short
The percentage of human faces detected in dogimg are=11.000% 

Question 2: This algorithmic choice necessitates that we communicate to the user that we accept human images only when they provide a clear view of a face (otherwise, we risk having unneccessarily frustrated users!). In your opinion, is this a reasonable expectation to pose on the user? If not, can you think of a way to detect humans in images that does not necessitate an image with a clearly presented face?

Answer:

Since no algorithm can give us 100% sureity that it only built to detect human faces.

In all human face detector algo there is atleast 5% probabiltiy that a non-human face is predicted as human face resulting in False positive and a human face sometimes not predicted due to not clearly presented huamn face in image resulting in True negative. So, i consider it is necessary to tell user beforehand that this algo is for human face detection based on facial feature,shape and size of human face.

One more thing to say to user is that the supplied human face image should be straight as above implemented Haar feature-based cascade classifiers to detect human faces in images is sensitive to rotation varience due the Standard Haar-like features are not rotated to identify rotated human faces.(look below images of girl's face as straight and rotated ).

Haar-like features have been used successfully in image sensors for face tracking and classification problems (Lai et al., 2001; Jones and Viola, 2003; Barreto et al., 2004; Huang and Lai, 2004), however other problems such as hand tracking (Barczak et al., 2005; Micilotta and Bowden, 2004; Kölsch and Turk, 2004) have not been so successful. The main reason for this is the fact that Haar-like features are not invariant over rotation. This means that any object that rotates and is sensitive to angle changes (such as hands) will be difficult to solve using standard Haar-like features. The features that define faces tend to be insensitive to small angle variations and Haar-like features have been used to detect head rotations of as much as 15o from the vertical (Jones and Viola, 2003). When people are standing their head is naturally aligned vertically with respect to gravity and so this rotational sensitivity tends not to be a significant problem for faces. Other body parts such as hands, arms and legs are not normally alligned with the horizontal or vertical axes so are difficult to model with traditional Haar-like features. Researchers have tended to use edge detection or colour based tracking of these parts (Messom et al., 2007). Several researchers have studied the impact of in plane rotations for image sensors with the use of twisted Haar-like feature (45o ) (Lienhart and Maydt, 2002; Lienhart et al., 2003a; 2003b) or diagonal features (Viola and Jones, 2001b) fairly good performance has been achieved. These techniques will have little benefit for problems that are sensitive to rotations, such as hand identification (Barczak et al., 2005; Kölsch and Turk, 2004; Antón-Canalís et al., 2005; Stenger et al, 2004; Wachs et al., 2005) which are not aligned to fixed angles (0o , 45o , 90o etc).

In [9]:
#load test files from dog-project/hooman_images
hooman1= "Hooman_images/hooman_straight.jpg"
hooman2= "Hooman_images/hooman_rotated.jpg"

def check(img_path):
    if(humanface_detector(img_path)):
        bounding_onhumanface(img_path)
        print("Hello human ur Face is detected")
    else:
        print("*****sorry******")
        img = cv2.imread(img_path)
        cv_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        plt.imshow(cv_rgb)
        plt.show()
        print("Face not detected")
        
check(hooman1)
Number of faces detected: 1
*************************
Hello human ur Face is detected
In [10]:
check(hooman2)
*****sorry******
Face not detected

Step 2: Detect Dogs

In this section, we use a pre-trained ResNet-50 model to detect dogs in images. Our first line of code downloads the ResNet-50 model, along with weights that have been trained on ImageNet, a very large, very popular dataset used for image classification and other vision tasks. ImageNet contains over 10 million URLs, each linking to an image containing an object from one of 1000 categories. Given an image, this pre-trained ResNet-50 model returns a prediction (derived from the available categories in ImageNet) for the object that is contained in the image.

In [8]:
from keras.applications.resnet50 import ResNet50

# define ResNet50 model
ResNet50_model = ResNet50(weights='imagenet')
Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels.h5
102858752/102853048 [==============================] - 3s 0us/step

Pre-process the Data

When using TensorFlow as backend, Keras CNNs require a 4D array (which we'll also refer to as a 4D tensor) as input, with shape

$$ (\text{nb_samples}, \text{rows}, \text{columns}, \text{channels}), $$

where nb_samples corresponds to the total number of images (or samples), and rows, columns, and channels correspond to the number of rows, columns, and channels for each image, respectively.

The path_to_tensor function below takes a string-valued file path to a color image as input and returns a 4D tensor suitable for supplying to a Keras CNN. The function first loads the image and resizes it to a square image that is $224 \times 224$ pixels. Next, the image is converted to an array, which is then resized to a 4D tensor. In this case, since we are working with color images, each image has three channels. Likewise, since we are processing a single image (or sample), the returned tensor will always have shape

$$ (1, 224, 224, 3). $$

The paths_to_tensor function takes a numpy array of string-valued image paths as input and returns a 4D tensor with shape

$$ (\text{nb_samples}, 224, 224, 3). $$

Here, nb_samples is the number of samples, or number of images, in the supplied array of image paths. It is best to think of nb_samples as the number of 3D tensors (where each 3D tensor corresponds to a different image) in your dataset!

In [9]:
from keras.preprocessing import image                  
from tqdm import tqdm

def path_to_tensor(img_path):
    # loads RGB image as PIL.Image.Image type
    img = image.load_img(img_path, target_size=(224, 224))
    # convert PIL.Image.Image type to 3D tensor with shape (224, 224, 3)
    x = image.img_to_array(img)
    # convert 3D tensor to 4D tensor with shape (1, 224, 224, 3) and return 4D tensor
    return np.expand_dims(x, axis=0)

def paths_to_tensor(img_paths):
    list_of_tensors = [path_to_tensor(img_path) for img_path in tqdm(img_paths)]
    return np.vstack(list_of_tensors)

Making Predictions with ResNet-50

Getting the 4D tensor ready for ResNet-50, and for any other pre-trained model in Keras, requires some additional processing. First, the RGB image is converted to BGR by reordering the channels. All pre-trained models have the additional normalization step that the mean pixel (expressed in RGB as $[103.939, 116.779, 123.68]$ and calculated from all pixels in all images in ImageNet) must be subtracted from every pixel in each image. This is implemented in the imported function preprocess_input. If you're curious, you can check the code for preprocess_input here.

Now that we have a way to format our image for supplying to ResNet-50, we are now ready to use the model to extract the predictions. This is accomplished with the predict method, which returns an array whose $i$-th entry is the model's predicted probability that the image belongs to the $i$-th ImageNet category. This is implemented in the ResNet50_predict_labels function below.

By taking the argmax of the predicted probability vector, we obtain an integer corresponding to the model's predicted object class, which we can identify with an object category through the use of this dictionary.

In [10]:
from keras.applications.resnet50 import preprocess_input, decode_predictions

def ResNet50_predict_labels(img_path):
    # returns prediction vector for image located at img_path
    img = preprocess_input(path_to_tensor(img_path))
    return np.argmax(ResNet50_model.predict(img))
In [14]:
img = preprocess_input(path_to_tensor(dog_files_short[0]))
img.shape
Out[14]:
(1, 224, 224, 3)

Write a Dog Detector

While looking at the dictionary, you will notice that the categories corresponding to dogs appear in an uninterrupted sequence and correspond to dictionary keys 151-268, inclusive, to include all categories from 'Chihuahua' to 'Mexican hairless'. Thus, in order to check to see if an image is predicted to contain a dog by the pre-trained ResNet-50 model, we need only check if the ResNet50_predict_labels function above returns a value between 151 and 268 (inclusive).

We use these ideas to complete the dog_detector function below, which returns True if a dog is detected in an image (and False if not).

In [11]:
### returns "True" if a dog is detected in the image stored at img_path
def dog_detector(img_path):
    prediction = ResNet50_predict_labels(img_path)
    return ((prediction <= 268) & (prediction >= 151)) 

(IMPLEMENTATION) Assess the Dog Detector

Question 3: Use the code cell below to test the performance of your dog_detector function.

  • What percentage of the images in human_files_short have a detected dog?
  • What percentage of the images in dog_files_short have a detected dog?

Answer:

What percentage of the images in human_files_short have a detected dog?

The percentage of dog faces detected in humanimg are= 0.000%

What percentage of the images in dog_files_short have a detected dog?

The percentage of dog faces detected in dogimg are= 100.000%

In [10]:
### TODO: Test the performance of the dog_detector function
### on the images in human_files_short and dog_files_short.
print("Testing the performance of the dog_detector function on the images in human_files_short")
count_dogdetectalgo_detect_dogface_in_humanimgs=0
for humanimg in human_files_short:
    if(dog_detector(humanimg)):
        count_dogdetectalgo_detect_dogface_in_humanimgs += 1
percentage_dog_face_detected_in_humanimg=((count_dogdetectalgo_detect_dogface_in_humanimgs)/len(human_files_short))*100
print("The percentage of dog faces detected in humanimg are={0:3.3f}%".format(percentage_dog_face_detected_in_humanimg))

print("Testing the performance of the dog_detector function on the images in dog_files_short")
count_dogdetectalgo_detect_dogface_in_dogimgs=0
for dogimg in dog_files_short:
    if(dog_detector(dogimg)):
        count_dogdetectalgo_detect_dogface_in_dogimgs += 1
percentage_dog_face_detected_in_dogimg=((count_dogdetectalgo_detect_dogface_in_dogimgs)/len(dog_files_short))*100
print("The percentage of dog faces detected in dogimg are={0:3.3f}% ".format(percentage_dog_face_detected_in_dogimg))
Testing the performance of the dog_detector function on the images in human_files_short
The percentage of dog faces detected in humanimg are=0.000%
Testing the performance of the dog_detector function on the images in dog_files_short
The percentage of dog faces detected in dogimg are=100.000% 

Step 3: Create a CNN to Classify Dog Breeds (from Scratch)

Now that we have functions for detecting humans and dogs in images, we need a way to predict breed from images. In this step, you will create a CNN that classifies dog breeds. You must create your CNN from scratch (so, you can't use transfer learning yet!), and you must attain a test accuracy of at least 1%. In Step 5 of this notebook, you will have the opportunity to use transfer learning to create a CNN that attains greatly improved accuracy.

Be careful with adding too many trainable layers! More parameters means longer training, which means you are more likely to need a GPU to accelerate the training process. Thankfully, Keras provides a handy estimate of the time that each epoch is likely to take; you can extrapolate this estimate to figure out how long it will take for your algorithm to train.

We mention that the task of assigning breed to dogs from images is considered exceptionally challenging. To see why, consider that even a human would have great difficulty in distinguishing between a Brittany and a Welsh Springer Spaniel.

Brittany Welsh Springer Spaniel

It is not difficult to find other dog breed pairs with minimal inter-class variation (for instance, Curly-Coated Retrievers and American Water Spaniels).

Curly-Coated Retriever American Water Spaniel

Likewise, recall that labradors come in yellow, chocolate, and black. Your vision-based algorithm will have to conquer this high intra-class variation to determine how to classify all of these different shades as the same breed.

Yellow Labrador Chocolate Labrador Black Labrador

We also mention that random chance presents an exceptionally low bar: setting aside the fact that the classes are slightly imabalanced, a random guess will provide a correct answer roughly 1 in 133 times, which corresponds to an accuracy of less than 1%.

Remember that the practice is far ahead of the theory in deep learning. Experiment with many different architectures, and trust your intuition. And, of course, have fun!

Pre-process the Data

We rescale the images by dividing every pixel in every image by 255.

In [12]:
from PIL import ImageFile                            
ImageFile.LOAD_TRUNCATED_IMAGES = True                 

# pre-process the data for Keras
train_tensors = paths_to_tensor(train_files).astype('float32')/255
valid_tensors = paths_to_tensor(valid_files).astype('float32')/255
test_tensors = paths_to_tensor(test_files).astype('float32')/255
100%|██████████| 6680/6680 [01:15<00:00, 88.99it/s] 
100%|██████████| 835/835 [00:08<00:00, 100.67it/s]
100%|██████████| 836/836 [00:08<00:00, 100.99it/s]

(IMPLEMENTATION) Model Architecture

Create a CNN to classify dog breed. At the end of your code cell block, summarize the layers of your model by executing the line:

    model.summary()

We have imported some Python modules to get you started, but feel free to import as many modules as you need. If you end up getting stuck, here's a hint that specifies a model that trains relatively fast on CPU and attains >1% test accuracy in 5 epochs:

Sample CNN

Question 4: Outline the steps you took to get to your final CNN architecture and your reasoning at each step. If you chose to use the hinted architecture above, describe why you think that CNN architecture should work well for the image classification task.

Answer: I choose to use above hinted arch. as series of convolutional layer with increasing filter size will allow the network to identify the increasingly complex pattern to better ditnisguish between different dog breed. The pooling layer is usefull to reduce the dimensionalty of convolutional layer it was getting and also reduce overfitting and increase validation accuracy.

In [13]:
from keras.layers import Conv2D, MaxPooling2D, GlobalAveragePooling2D
from keras.layers import Dropout, Flatten, Dense
from keras.models import Sequential

model = Sequential()

### TODO: Define your architecture.
#train_tensors.shape=(6680, 224, 224, 3)

model.add(Conv2D(filters=16, kernel_size=2, padding='same', activation='relu', 
                        input_shape=(224, 224, 3)))
model.add(MaxPooling2D(pool_size=2))
model.add(Conv2D(filters=32, kernel_size=2, padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=2))
model.add(Conv2D(filters=64, kernel_size=2, padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=2))
model.add(GlobalAveragePooling2D())
model.add(Dense(len(dog_names),activation="softmax"))
model.summary()
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_1 (Conv2D)            (None, 224, 224, 16)      208       
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 112, 112, 16)      0         
_________________________________________________________________
conv2d_2 (Conv2D)            (None, 112, 112, 32)      2080      
_________________________________________________________________
max_pooling2d_3 (MaxPooling2 (None, 56, 56, 32)        0         
_________________________________________________________________
conv2d_3 (Conv2D)            (None, 56, 56, 64)        8256      
_________________________________________________________________
max_pooling2d_4 (MaxPooling2 (None, 28, 28, 64)        0         
_________________________________________________________________
global_average_pooling2d_1 ( (None, 64)                0         
_________________________________________________________________
dense_1 (Dense)              (None, 133)               8645      
=================================================================
Total params: 19,189
Trainable params: 19,189
Non-trainable params: 0
_________________________________________________________________

Compile the Model

In [14]:
model.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['accuracy'])

(IMPLEMENTATION) Train the Model

Train your model in the code cell below. Use model checkpointing to save the model that attains the best validation loss.

You are welcome to augment the training data, but this is not a requirement.

In [18]:
from keras.callbacks import ModelCheckpoint  

### TODO: specify the number of epochs that you would like to use to train the model.

epochs = 10

### Do NOT modify the code below this line.

checkpointer = ModelCheckpoint(filepath='saved_models2/weights.best.from_scratch.hdf5', 
                               verbose=1, save_best_only=True)

model.fit(train_tensors, train_targets, 
          validation_data=(valid_tensors, valid_targets),
          epochs=epochs, batch_size=20, callbacks=[checkpointer], verbose=1)
Train on 6680 samples, validate on 835 samples
Epoch 1/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.8835 - acc: 0.0081Epoch 00001: val_loss improved from inf to 4.87083, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 22s 3ms/step - loss: 4.8835 - acc: 0.0081 - val_loss: 4.8708 - val_acc: 0.0108
Epoch 2/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.8690 - acc: 0.0086Epoch 00002: val_loss improved from 4.87083 to 4.86213, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.8691 - acc: 0.0085 - val_loss: 4.8621 - val_acc: 0.0120
Epoch 3/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.8468 - acc: 0.0144Epoch 00003: val_loss improved from 4.86213 to 4.83081, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.8470 - acc: 0.0144 - val_loss: 4.8308 - val_acc: 0.0144
Epoch 4/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.7923 - acc: 0.0215Epoch 00004: val_loss improved from 4.83081 to 4.78709, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.7928 - acc: 0.0214 - val_loss: 4.7871 - val_acc: 0.0216
Epoch 5/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.7523 - acc: 0.0204Epoch 00005: val_loss improved from 4.78709 to 4.76332, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.7527 - acc: 0.0204 - val_loss: 4.7633 - val_acc: 0.0216
Epoch 6/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.7251 - acc: 0.0269Epoch 00006: val_loss improved from 4.76332 to 4.75332, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.7252 - acc: 0.0268 - val_loss: 4.7533 - val_acc: 0.0251
Epoch 7/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.6976 - acc: 0.0272Epoch 00007: val_loss improved from 4.75332 to 4.72692, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.6984 - acc: 0.0271 - val_loss: 4.7269 - val_acc: 0.0335
Epoch 8/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.6712 - acc: 0.0327Epoch 00008: val_loss improved from 4.72692 to 4.72575, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.6704 - acc: 0.0328 - val_loss: 4.7258 - val_acc: 0.0275
Epoch 9/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.6415 - acc: 0.0348Epoch 00009: val_loss improved from 4.72575 to 4.71126, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.6417 - acc: 0.0349 - val_loss: 4.7113 - val_acc: 0.0251
Epoch 10/10
6660/6680 [============================>.] - ETA: 0s - loss: 4.6147 - acc: 0.0351Epoch 00010: val_loss improved from 4.71126 to 4.68738, saving model to saved_models2/weights.best.from_scratch.hdf5
6680/6680 [==============================] - 21s 3ms/step - loss: 4.6143 - acc: 0.0350 - val_loss: 4.6874 - val_acc: 0.0335
Out[18]:
<keras.callbacks.History at 0x7f8d62f97518>

Load the Model with the Best Validation Loss

In [14]:
model.load_weights('saved_models2/weights.best.from_scratch.hdf5')

Test the Model

Try out your model on the test dataset of dog images. Ensure that your test accuracy is greater than 1%.

In [15]:
# get index of predicted dog breed for each image in test set
dog_breed_predictions = [np.argmax(model.predict(np.expand_dims(tensor, axis=0))) for tensor in test_tensors]

# report test accuracy
test_accuracy = 100*np.sum(np.array(dog_breed_predictions)==np.argmax(test_targets, axis=1))/len(dog_breed_predictions)
#https://youtu.be/3sDYifgjFck?t=56 follow this
print('Test accuracy: %.4f%%' % test_accuracy)
Test accuracy: 4.1866%
In [16]:
train_tensors.shape
Out[16]:
(6680, 224, 224, 3)

Step 4: Use a CNN to Classify Dog Breeds

To reduce training time without sacrificing accuracy, we show you how to train a CNN using transfer learning. In the following step, you will get a chance to use transfer learning to train your own CNN.

Obtain Bottleneck Features

In [15]:
bottleneck_features = np.load('/data/bottleneck_features/DogVGG16Data.npz')
train_VGG16 = bottleneck_features['train']
valid_VGG16 = bottleneck_features['valid']
test_VGG16 = bottleneck_features['test']
In [30]:
train_VGG16.shape #this parameters and weights will be the input to new layer for training data..
Out[30]:
(6680, 7, 7, 512)

Model Architecture

The model uses the the pre-trained VGG-16 model as a fixed feature extractor, where the last convolutional output of VGG-16 is fed as input to our model. We only add a global average pooling layer and a fully connected layer, where the latter contains one node for each dog category and is equipped with a softmax.

In [16]:
VGG16_model = Sequential()
VGG16_model.add(GlobalAveragePooling2D(input_shape=train_VGG16.shape[1:]))
VGG16_model.add(Dense(133, activation='softmax'))

VGG16_model.summary()
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
global_average_pooling2d_2 ( (None, 512)               0         
_________________________________________________________________
dense_2 (Dense)              (None, 133)               68229     
=================================================================
Total params: 68,229
Trainable params: 68,229
Non-trainable params: 0
_________________________________________________________________

Compile the Model

In [17]:
VGG16_model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy'])

Train the Model

In [20]:
### TODO: Train the model.
from keras.callbacks import ModelCheckpoint  

batch_size = [20,35,37,40]
epochs = [20,35,40,50]

fitingdict_vgg16={'Batch_Size':[], 
            'Epochs':[],
            'Test_Accuracy':[]}

for bs in batch_size:
    for ep in epochs:
        checkpointer = ModelCheckpoint(filepath='saved_models1/weights.best.vgg16_bs'+str(bs)+'_ep'+str(ep)+'.hdf5', 
                               verbose=1, save_best_only=True)
        print("\nBatch size={0} Epoch={1}".format(bs,ep))
        VGG16_model.fit(train_VGG16, train_targets,validation_data=(valid_VGG16, valid_targets),
                          epochs=ep , batch_size=bs,
                          callbacks=[checkpointer],verbose=1)

        #LOAD the model with Best validation loss
        VGG16_model.load_weights('saved_models1/weights.best.vgg16_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')

        
        VGG16_predictions = [np.argmax(VGG16_model.predict(np.expand_dims(feature, axis=0))) for feature in test_VGG16]
        test_accuracy = 100*np.sum(np.array(VGG16_predictions)==np.argmax(test_targets, axis=1))/len(VGG16_predictions)
        fitingdict_vgg16['Batch_Size'].append(bs)
        fitingdict_vgg16['Epochs'].append(ep)
        fitingdict_vgg16['Test_Accuracy'].append(test_accuracy)
Batch size=20 Epoch=20
Train on 6680 samples, validate on 835 samples
Epoch 1/20
6640/6680 [============================>.] - ETA: 0s - loss: 12.2849 - acc: 0.1268Epoch 00001: val_loss improved from inf to 10.73861, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 316us/step - loss: 12.2704 - acc: 0.1277 - val_loss: 10.7386 - val_acc: 0.2024
Epoch 2/20
6660/6680 [============================>.] - ETA: 0s - loss: 9.7665 - acc: 0.2959Epoch 00002: val_loss improved from 10.73861 to 9.56120, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 257us/step - loss: 9.7663 - acc: 0.2963 - val_loss: 9.5612 - val_acc: 0.2982
Epoch 3/20
6520/6680 [============================>.] - ETA: 0s - loss: 9.0206 - acc: 0.3758Epoch 00003: val_loss improved from 9.56120 to 9.32497, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 9.0173 - acc: 0.3759 - val_loss: 9.3250 - val_acc: 0.3257
Epoch 4/20
6480/6680 [============================>.] - ETA: 0s - loss: 8.7739 - acc: 0.4105Epoch 00004: val_loss improved from 9.32497 to 9.16428, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 8.7702 - acc: 0.4103 - val_loss: 9.1643 - val_acc: 0.3473
Epoch 5/20
6460/6680 [============================>.] - ETA: 0s - loss: 8.4450 - acc: 0.4353Epoch 00005: val_loss improved from 9.16428 to 8.77212, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 8.4474 - acc: 0.4346 - val_loss: 8.7721 - val_acc: 0.3737
Epoch 6/20
6500/6680 [============================>.] - ETA: 0s - loss: 8.1363 - acc: 0.4585Epoch 00006: val_loss improved from 8.77212 to 8.64753, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 8.1527 - acc: 0.4575 - val_loss: 8.6475 - val_acc: 0.3808
Epoch 7/20
6460/6680 [============================>.] - ETA: 0s - loss: 8.0196 - acc: 0.4746Epoch 00007: val_loss improved from 8.64753 to 8.58411, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 254us/step - loss: 8.0126 - acc: 0.4750 - val_loss: 8.5841 - val_acc: 0.3832
Epoch 8/20
6660/6680 [============================>.] - ETA: 0s - loss: 7.9130 - acc: 0.4859Epoch 00008: val_loss improved from 8.58411 to 8.48738, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 254us/step - loss: 7.9183 - acc: 0.4856 - val_loss: 8.4874 - val_acc: 0.3916
Epoch 9/20
6660/6680 [============================>.] - ETA: 0s - loss: 7.8093 - acc: 0.4935Epoch 00009: val_loss improved from 8.48738 to 8.48704, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 7.8138 - acc: 0.4931 - val_loss: 8.4870 - val_acc: 0.3940
Epoch 10/20
6640/6680 [============================>.] - ETA: 0s - loss: 7.7342 - acc: 0.5005Epoch 00010: val_loss improved from 8.48704 to 8.42266, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 254us/step - loss: 7.7386 - acc: 0.5003 - val_loss: 8.4227 - val_acc: 0.3964
Epoch 11/20
6520/6680 [============================>.] - ETA: 0s - loss: 7.6543 - acc: 0.5109Epoch 00011: val_loss improved from 8.42266 to 8.36733, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 7.6441 - acc: 0.5112 - val_loss: 8.3673 - val_acc: 0.4048
Epoch 12/20
6620/6680 [============================>.] - ETA: 0s - loss: 7.6121 - acc: 0.5181Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 7.6091 - acc: 0.5181 - val_loss: 8.3853 - val_acc: 0.4072
Epoch 13/20
6500/6680 [============================>.] - ETA: 0s - loss: 7.5441 - acc: 0.5202Epoch 00013: val_loss improved from 8.36733 to 8.28634, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 7.5376 - acc: 0.5208 - val_loss: 8.2863 - val_acc: 0.4096
Epoch 14/20
6460/6680 [============================>.] - ETA: 0s - loss: 7.4309 - acc: 0.5300Epoch 00014: val_loss improved from 8.28634 to 8.14191, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 253us/step - loss: 7.4346 - acc: 0.5296 - val_loss: 8.1419 - val_acc: 0.4240
Epoch 15/20
6520/6680 [============================>.] - ETA: 0s - loss: 7.3041 - acc: 0.5314Epoch 00015: val_loss improved from 8.14191 to 8.03198, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 7.2951 - acc: 0.5316 - val_loss: 8.0320 - val_acc: 0.4156
Epoch 16/20
6640/6680 [============================>.] - ETA: 0s - loss: 7.1039 - acc: 0.5453Epoch 00016: val_loss improved from 8.03198 to 7.92229, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 255us/step - loss: 7.1048 - acc: 0.5454 - val_loss: 7.9223 - val_acc: 0.4144
Epoch 17/20
6500/6680 [============================>.] - ETA: 0s - loss: 7.0511 - acc: 0.5526Epoch 00017: val_loss improved from 7.92229 to 7.80997, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 7.0452 - acc: 0.5530 - val_loss: 7.8100 - val_acc: 0.4383
Epoch 18/20
6640/6680 [============================>.] - ETA: 0s - loss: 6.9734 - acc: 0.5557Epoch 00018: val_loss improved from 7.80997 to 7.73699, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 254us/step - loss: 6.9709 - acc: 0.5558 - val_loss: 7.7370 - val_acc: 0.4299
Epoch 19/20
6640/6680 [============================>.] - ETA: 0s - loss: 6.8487 - acc: 0.5640Epoch 00019: val_loss improved from 7.73699 to 7.67507, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 257us/step - loss: 6.8464 - acc: 0.5642 - val_loss: 7.6751 - val_acc: 0.4503
Epoch 20/20
6640/6680 [============================>.] - ETA: 0s - loss: 6.7425 - acc: 0.5745Epoch 00020: val_loss improved from 7.67507 to 7.61237, saving model to saved_models1/weights.best.vgg16_bs20_ep20.hdf5
6680/6680 [==============================] - 2s 253us/step - loss: 6.7553 - acc: 0.5738 - val_loss: 7.6124 - val_acc: 0.4587

Batch size=20 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6480/6680 [============================>.] - ETA: 0s - loss: 6.7527 - acc: 0.5753Epoch 00001: val_loss improved from inf to 7.63061, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 6.7377 - acc: 0.5762 - val_loss: 7.6306 - val_acc: 0.4515
Epoch 2/35
6480/6680 [============================>.] - ETA: 0s - loss: 6.7121 - acc: 0.5755Epoch 00002: val_loss improved from 7.63061 to 7.56560, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 6.6910 - acc: 0.5763 - val_loss: 7.5656 - val_acc: 0.4527
Epoch 3/35
6500/6680 [============================>.] - ETA: 0s - loss: 6.5811 - acc: 0.5822Epoch 00003: val_loss improved from 7.56560 to 7.44745, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 6.5799 - acc: 0.5825 - val_loss: 7.4475 - val_acc: 0.4611
Epoch 4/35
6660/6680 [============================>.] - ETA: 0s - loss: 6.5353 - acc: 0.5889Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 6.5304 - acc: 0.5891 - val_loss: 7.4680 - val_acc: 0.4695
Epoch 5/35
6520/6680 [============================>.] - ETA: 0s - loss: 6.4319 - acc: 0.5896Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 6.4369 - acc: 0.5889 - val_loss: 7.5604 - val_acc: 0.4539
Epoch 6/35
6480/6680 [============================>.] - ETA: 0s - loss: 6.3749 - acc: 0.5968Epoch 00006: val_loss improved from 7.44745 to 7.36995, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 6.3789 - acc: 0.5967 - val_loss: 7.3700 - val_acc: 0.4671
Epoch 7/35
6580/6680 [============================>.] - ETA: 0s - loss: 6.3626 - acc: 0.5983Epoch 00007: val_loss improved from 7.36995 to 7.35530, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 250us/step - loss: 6.3519 - acc: 0.5991 - val_loss: 7.3553 - val_acc: 0.4659
Epoch 8/35
6480/6680 [============================>.] - ETA: 0s - loss: 6.3235 - acc: 0.6020Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 6.3257 - acc: 0.6019 - val_loss: 7.3729 - val_acc: 0.4707
Epoch 9/35
6580/6680 [============================>.] - ETA: 0s - loss: 6.2815 - acc: 0.6015Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 6.2895 - acc: 0.6009 - val_loss: 7.3566 - val_acc: 0.4719
Epoch 10/35
6580/6680 [============================>.] - ETA: 0s - loss: 6.1421 - acc: 0.6081Epoch 00010: val_loss improved from 7.35530 to 7.30314, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 251us/step - loss: 6.1543 - acc: 0.6072 - val_loss: 7.3031 - val_acc: 0.4659
Epoch 11/35
6560/6680 [============================>.] - ETA: 0s - loss: 6.0993 - acc: 0.6142Epoch 00011: val_loss improved from 7.30314 to 7.24965, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 250us/step - loss: 6.1104 - acc: 0.6136 - val_loss: 7.2497 - val_acc: 0.4754
Epoch 12/35
6480/6680 [============================>.] - ETA: 0s - loss: 6.0601 - acc: 0.6151Epoch 00012: val_loss improved from 7.24965 to 7.11197, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 6.0437 - acc: 0.6162 - val_loss: 7.1120 - val_acc: 0.4814
Epoch 13/35
6600/6680 [============================>.] - ETA: 0s - loss: 5.9624 - acc: 0.6227Epoch 00013: val_loss improved from 7.11197 to 7.06896, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 249us/step - loss: 5.9803 - acc: 0.6217 - val_loss: 7.0690 - val_acc: 0.4838
Epoch 14/35
6460/6680 [============================>.] - ETA: 0s - loss: 5.9562 - acc: 0.6246Epoch 00014: val_loss improved from 7.06896 to 7.02231, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 251us/step - loss: 5.9641 - acc: 0.6241 - val_loss: 7.0223 - val_acc: 0.4886
Epoch 15/35
6500/6680 [============================>.] - ETA: 0s - loss: 5.9696 - acc: 0.6249Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.9518 - acc: 0.6257 - val_loss: 7.0988 - val_acc: 0.4874
Epoch 16/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.9491 - acc: 0.6262Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.9418 - acc: 0.6268 - val_loss: 7.0677 - val_acc: 0.4934
Epoch 17/35
6500/6680 [============================>.] - ETA: 0s - loss: 5.9558 - acc: 0.6262Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.9401 - acc: 0.6272 - val_loss: 7.0414 - val_acc: 0.4934
Epoch 18/35
6460/6680 [============================>.] - ETA: 0s - loss: 5.9518 - acc: 0.6280Epoch 00018: val_loss improved from 7.02231 to 7.01481, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.9391 - acc: 0.6289 - val_loss: 7.0148 - val_acc: 0.4958
Epoch 19/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.9467 - acc: 0.6274Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 5.9307 - acc: 0.6283 - val_loss: 7.1441 - val_acc: 0.4934
Epoch 20/35
6460/6680 [============================>.] - ETA: 0s - loss: 5.8875 - acc: 0.6277Epoch 00020: val_loss improved from 7.01481 to 6.99397, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.8822 - acc: 0.6281 - val_loss: 6.9940 - val_acc: 0.5042
Epoch 21/35
6480/6680 [============================>.] - ETA: 0s - loss: 5.8406 - acc: 0.6338Epoch 00021: val_loss improved from 6.99397 to 6.97883, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.8324 - acc: 0.6341 - val_loss: 6.9788 - val_acc: 0.4958
Epoch 22/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.8655 - acc: 0.6337Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 5.8296 - acc: 0.6359 - val_loss: 6.9797 - val_acc: 0.4982
Epoch 23/35
6540/6680 [============================>.] - ETA: 0s - loss: 5.8313 - acc: 0.6343Epoch 00023: val_loss improved from 6.97883 to 6.95965, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 251us/step - loss: 5.8284 - acc: 0.6343 - val_loss: 6.9596 - val_acc: 0.5018
Epoch 24/35
6640/6680 [============================>.] - ETA: 0s - loss: 5.8228 - acc: 0.6360Epoch 00024: val_loss improved from 6.95965 to 6.94867, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 254us/step - loss: 5.8197 - acc: 0.6361 - val_loss: 6.9487 - val_acc: 0.4970
Epoch 25/35
6460/6680 [============================>.] - ETA: 0s - loss: 5.8139 - acc: 0.6370Epoch 00025: val_loss improved from 6.94867 to 6.92395, saving model to saved_models1/weights.best.vgg16_bs20_ep35.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.8155 - acc: 0.6370 - val_loss: 6.9239 - val_acc: 0.5054
Epoch 26/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.7984 - acc: 0.6383Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8154 - acc: 0.6373 - val_loss: 6.9685 - val_acc: 0.4946
Epoch 27/35
6620/6680 [============================>.] - ETA: 0s - loss: 5.8188 - acc: 0.6376Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 2s 248us/step - loss: 5.8100 - acc: 0.6382 - val_loss: 7.0006 - val_acc: 0.4946
Epoch 28/35
6540/6680 [============================>.] - ETA: 0s - loss: 5.8034 - acc: 0.6387Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8097 - acc: 0.6383 - val_loss: 7.0077 - val_acc: 0.4982
Epoch 29/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.8084 - acc: 0.6380Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8127 - acc: 0.6377 - val_loss: 7.0003 - val_acc: 0.4874
Epoch 30/35
6500/6680 [============================>.] - ETA: 0s - loss: 5.7806 - acc: 0.6400Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8083 - acc: 0.6383 - val_loss: 7.0214 - val_acc: 0.4934
Epoch 31/35
6500/6680 [============================>.] - ETA: 0s - loss: 5.7889 - acc: 0.6398Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8090 - acc: 0.6386 - val_loss: 7.0100 - val_acc: 0.4922
Epoch 32/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.7916 - acc: 0.6390Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 5.8107 - acc: 0.6379 - val_loss: 6.9448 - val_acc: 0.5090
Epoch 33/35
6460/6680 [============================>.] - ETA: 0s - loss: 5.8106 - acc: 0.6385Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8050 - acc: 0.6389 - val_loss: 7.0753 - val_acc: 0.4994
Epoch 34/35
6640/6680 [============================>.] - ETA: 0s - loss: 5.7994 - acc: 0.6396Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8062 - acc: 0.6391 - val_loss: 7.0301 - val_acc: 0.4982
Epoch 35/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.8049 - acc: 0.6392Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8093 - acc: 0.6389 - val_loss: 7.0263 - val_acc: 0.5102

Batch size=20 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.8101 - acc: 0.6378Epoch 00001: val_loss improved from inf to 6.97348, saving model to saved_models1/weights.best.vgg16_bs20_ep40.hdf5
6680/6680 [==============================] - 2s 253us/step - loss: 5.8120 - acc: 0.6377 - val_loss: 6.9735 - val_acc: 0.5018
Epoch 2/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.8191 - acc: 0.6373Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8112 - acc: 0.6377 - val_loss: 6.9982 - val_acc: 0.5018
Epoch 3/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.8087 - acc: 0.6379Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8128 - acc: 0.6377 - val_loss: 7.0417 - val_acc: 0.4874
Epoch 4/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.7907 - acc: 0.6393Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8105 - acc: 0.6380 - val_loss: 7.0377 - val_acc: 0.4946
Epoch 5/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.8067 - acc: 0.6386Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8090 - acc: 0.6385 - val_loss: 7.0683 - val_acc: 0.4862
Epoch 6/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.8255 - acc: 0.6372Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8127 - acc: 0.6380 - val_loss: 6.9991 - val_acc: 0.4970
Epoch 7/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.7969 - acc: 0.6397Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8094 - acc: 0.6386 - val_loss: 6.9921 - val_acc: 0.5042
Epoch 8/40
6540/6680 [============================>.] - ETA: 0s - loss: 5.8161 - acc: 0.6381Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8125 - acc: 0.6383 - val_loss: 7.0207 - val_acc: 0.4982
Epoch 9/40
6640/6680 [============================>.] - ETA: 0s - loss: 5.8081 - acc: 0.6389Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8095 - acc: 0.6388 - val_loss: 7.0493 - val_acc: 0.4910
Epoch 10/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.8204 - acc: 0.6380Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 2s 248us/step - loss: 5.8086 - acc: 0.6388 - val_loss: 7.0098 - val_acc: 0.4994
Epoch 11/40
6640/6680 [============================>.] - ETA: 0s - loss: 5.8114 - acc: 0.6380Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8080 - acc: 0.6382 - val_loss: 7.0471 - val_acc: 0.4946
Epoch 12/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.8131 - acc: 0.6384Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8053 - acc: 0.6389 - val_loss: 7.0390 - val_acc: 0.5030
Epoch 13/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.8001 - acc: 0.6392Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8078 - acc: 0.6388 - val_loss: 7.0246 - val_acc: 0.5006
Epoch 14/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.8071 - acc: 0.6392Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8089 - acc: 0.6391 - val_loss: 7.0758 - val_acc: 0.4982
Epoch 15/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.7673 - acc: 0.6415Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8046 - acc: 0.6392 - val_loss: 7.0242 - val_acc: 0.5006
Epoch 16/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.8293 - acc: 0.6375Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.8043 - acc: 0.6391 - val_loss: 7.0295 - val_acc: 0.5066
Epoch 17/40
6640/6680 [============================>.] - ETA: 0s - loss: 5.8217 - acc: 0.6380Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.8085 - acc: 0.6388 - val_loss: 7.0546 - val_acc: 0.4886
Epoch 18/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.8020 - acc: 0.6392Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.8024 - acc: 0.6392 - val_loss: 7.0540 - val_acc: 0.4982
Epoch 19/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.7943 - acc: 0.6378Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7758 - acc: 0.6391 - val_loss: 7.0433 - val_acc: 0.4970
Epoch 20/40
6540/6680 [============================>.] - ETA: 0s - loss: 5.7275 - acc: 0.6425Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7162 - acc: 0.6431 - val_loss: 6.9876 - val_acc: 0.5078
Epoch 21/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.7091 - acc: 0.6449Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7113 - acc: 0.6448 - val_loss: 7.0182 - val_acc: 0.4982
Epoch 22/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.7361 - acc: 0.6428Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.7094 - acc: 0.6445 - val_loss: 7.0028 - val_acc: 0.5018
Epoch 23/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.6955 - acc: 0.6460Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7061 - acc: 0.6454 - val_loss: 6.9924 - val_acc: 0.5042
Epoch 24/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.7130 - acc: 0.6447Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7058 - acc: 0.6452 - val_loss: 7.0113 - val_acc: 0.5030
Epoch 25/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.6970 - acc: 0.6460Epoch 00025: val_loss improved from 6.97348 to 6.94948, saving model to saved_models1/weights.best.vgg16_bs20_ep40.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.7051 - acc: 0.6455 - val_loss: 6.9495 - val_acc: 0.5042
Epoch 26/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.6991 - acc: 0.6461Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.7046 - acc: 0.6458 - val_loss: 6.9543 - val_acc: 0.5042
Epoch 27/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.7026 - acc: 0.6454Epoch 00027: val_loss improved from 6.94948 to 6.93504, saving model to saved_models1/weights.best.vgg16_bs20_ep40.hdf5
6680/6680 [==============================] - 2s 253us/step - loss: 5.7054 - acc: 0.6452 - val_loss: 6.9350 - val_acc: 0.5054
Epoch 28/40
6620/6680 [============================>.] - ETA: 0s - loss: 5.7167 - acc: 0.6444Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.7064 - acc: 0.6451 - val_loss: 6.9522 - val_acc: 0.5078
Epoch 29/40
6500/6680 [============================>.] - ETA: 0s - loss: 5.6977 - acc: 0.6455Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.7082 - acc: 0.6449 - val_loss: 6.9490 - val_acc: 0.4994
Epoch 30/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.6980 - acc: 0.6463Epoch 00030: val_loss improved from 6.93504 to 6.91137, saving model to saved_models1/weights.best.vgg16_bs20_ep40.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.7011 - acc: 0.6461 - val_loss: 6.9114 - val_acc: 0.5054
Epoch 31/40
6540/6680 [============================>.] - ETA: 0s - loss: 5.7165 - acc: 0.6448Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.7053 - acc: 0.6455 - val_loss: 6.9656 - val_acc: 0.5042
Epoch 32/40
6460/6680 [============================>.] - ETA: 0s - loss: 5.7016 - acc: 0.6457Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 2s 254us/step - loss: 5.7020 - acc: 0.6457 - val_loss: 6.9697 - val_acc: 0.5042
Epoch 33/40
6580/6680 [============================>.] - ETA: 0s - loss: 5.6943 - acc: 0.6459Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 2s 262us/step - loss: 5.7032 - acc: 0.6454 - val_loss: 6.9606 - val_acc: 0.4970
Epoch 34/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6944 - acc: 0.6459Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 2s 261us/step - loss: 5.7010 - acc: 0.6455 - val_loss: 6.9941 - val_acc: 0.5030
Epoch 35/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6861 - acc: 0.6452Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 2s 262us/step - loss: 5.6928 - acc: 0.6448 - val_loss: 7.0507 - val_acc: 0.5006
Epoch 36/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6705 - acc: 0.6438Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 2s 262us/step - loss: 5.6678 - acc: 0.6440 - val_loss: 6.9767 - val_acc: 0.5006
Epoch 37/40
6620/6680 [============================>.] - ETA: 0s - loss: 5.6428 - acc: 0.6473Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 2s 260us/step - loss: 5.6452 - acc: 0.6472 - val_loss: 6.9230 - val_acc: 0.5030
Epoch 38/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6485 - acc: 0.6471Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 2s 259us/step - loss: 5.6316 - acc: 0.6481 - val_loss: 6.9211 - val_acc: 0.5090
Epoch 39/40
6620/6680 [============================>.] - ETA: 0s - loss: 5.6294 - acc: 0.6486Epoch 00039: val_loss improved from 6.91137 to 6.85904, saving model to saved_models1/weights.best.vgg16_bs20_ep40.hdf5
6680/6680 [==============================] - 2s 264us/step - loss: 5.6238 - acc: 0.6490 - val_loss: 6.8590 - val_acc: 0.5066
Epoch 40/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6215 - acc: 0.6491Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 2s 264us/step - loss: 5.6193 - acc: 0.6493 - val_loss: 6.8874 - val_acc: 0.5030

Batch size=20 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6500/6680 [============================>.] - ETA: 0s - loss: 5.6236 - acc: 0.6494Epoch 00001: val_loss improved from inf to 6.86228, saving model to saved_models1/weights.best.vgg16_bs20_ep50.hdf5
6680/6680 [==============================] - 2s 251us/step - loss: 5.6193 - acc: 0.6497 - val_loss: 6.8623 - val_acc: 0.5090
Epoch 2/50
6540/6680 [============================>.] - ETA: 0s - loss: 5.6337 - acc: 0.6486Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 5.6127 - acc: 0.6499 - val_loss: 6.8927 - val_acc: 0.5078
Epoch 3/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.5925 - acc: 0.6519Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6092 - acc: 0.6506 - val_loss: 6.9195 - val_acc: 0.4970
Epoch 4/50
6500/6680 [============================>.] - ETA: 0s - loss: 5.6022 - acc: 0.6508Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6129 - acc: 0.6501 - val_loss: 6.8660 - val_acc: 0.4982
Epoch 5/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6085 - acc: 0.6506Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6069 - acc: 0.6507 - val_loss: 6.8889 - val_acc: 0.5042
Epoch 6/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6512Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6049 - acc: 0.6515 - val_loss: 6.9809 - val_acc: 0.4970
Epoch 7/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6143 - acc: 0.6506Epoch 00007: val_loss improved from 6.86228 to 6.85760, saving model to saved_models1/weights.best.vgg16_bs20_ep50.hdf5
6680/6680 [==============================] - 2s 251us/step - loss: 5.6070 - acc: 0.6510 - val_loss: 6.8576 - val_acc: 0.5090
Epoch 8/50
6540/6680 [============================>.] - ETA: 0s - loss: 5.6167 - acc: 0.6509Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6027 - acc: 0.6518 - val_loss: 6.9685 - val_acc: 0.5006
Epoch 9/50
6540/6680 [============================>.] - ETA: 0s - loss: 5.6001 - acc: 0.6517Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6058 - acc: 0.6513 - val_loss: 6.8841 - val_acc: 0.5018
Epoch 10/50
6620/6680 [============================>.] - ETA: 0s - loss: 5.5968 - acc: 0.6521Epoch 00010: val_loss improved from 6.85760 to 6.85536, saving model to saved_models1/weights.best.vgg16_bs20_ep50.hdf5
6680/6680 [==============================] - 2s 258us/step - loss: 5.6045 - acc: 0.6516 - val_loss: 6.8554 - val_acc: 0.5042
Epoch 11/50
6640/6680 [============================>.] - ETA: 0s - loss: 5.6054 - acc: 0.6517Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 2s 254us/step - loss: 5.6032 - acc: 0.6518 - val_loss: 6.8731 - val_acc: 0.5114
Epoch 12/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.5978 - acc: 0.6520Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6041 - acc: 0.6516 - val_loss: 6.9051 - val_acc: 0.5018
Epoch 13/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6518Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6040 - acc: 0.6521 - val_loss: 6.8800 - val_acc: 0.5030
Epoch 14/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5864 - acc: 0.6531Epoch 00014: val_loss improved from 6.85536 to 6.84438, saving model to saved_models1/weights.best.vgg16_bs20_ep50.hdf5
6680/6680 [==============================] - 2s 252us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8444 - val_acc: 0.5102
Epoch 15/50
6500/6680 [============================>.] - ETA: 0s - loss: 5.6025 - acc: 0.6517Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6035 - acc: 0.6516 - val_loss: 6.8538 - val_acc: 0.5078
Epoch 16/50
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6108 - acc: 0.6514Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8618 - val_acc: 0.5102
Epoch 17/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6027 - acc: 0.6520Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6053 - acc: 0.6518 - val_loss: 6.8877 - val_acc: 0.5114
Epoch 18/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6183 - acc: 0.6512Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6040 - acc: 0.6521 - val_loss: 6.9141 - val_acc: 0.5066
Epoch 19/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6259 - acc: 0.6503Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6029 - acc: 0.6516 - val_loss: 6.8703 - val_acc: 0.5198
Epoch 20/50
6500/6680 [============================>.] - ETA: 0s - loss: 5.6243 - acc: 0.6503Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6055 - acc: 0.6515 - val_loss: 6.8752 - val_acc: 0.5162
Epoch 21/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6237 - acc: 0.6503Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6037 - acc: 0.6515 - val_loss: 6.8614 - val_acc: 0.5150
Epoch 22/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6189 - acc: 0.6509Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 2s 249us/step - loss: 5.6027 - acc: 0.6519 - val_loss: 6.8699 - val_acc: 0.5114
Epoch 23/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.5987 - acc: 0.6522Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8861 - val_acc: 0.5078
Epoch 24/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.5674 - acc: 0.6543Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6044 - acc: 0.6519 - val_loss: 6.8636 - val_acc: 0.5162
Epoch 25/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6322 - acc: 0.6498Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6035 - acc: 0.6516 - val_loss: 6.9273 - val_acc: 0.5102
Epoch 26/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6000 - acc: 0.6520Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6037 - acc: 0.6518 - val_loss: 6.9008 - val_acc: 0.5126
Epoch 27/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6517Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6055 - acc: 0.6516 - val_loss: 6.8891 - val_acc: 0.5054
Epoch 28/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6110 - acc: 0.6517Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6038 - acc: 0.6521 - val_loss: 6.8867 - val_acc: 0.5138
Epoch 29/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.5969 - acc: 0.6523Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6055 - acc: 0.6518 - val_loss: 6.9275 - val_acc: 0.5090
Epoch 30/50
6620/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6517Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.9071 - val_acc: 0.5102
Epoch 31/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6134 - acc: 0.6511Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6047 - acc: 0.6516 - val_loss: 6.8817 - val_acc: 0.5090
Epoch 32/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6100 - acc: 0.6512Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6024 - acc: 0.6516 - val_loss: 6.8849 - val_acc: 0.5186
Epoch 33/50
6640/6680 [============================>.] - ETA: 0s - loss: 5.6003 - acc: 0.6523Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6030 - acc: 0.6521 - val_loss: 6.8701 - val_acc: 0.5114
Epoch 34/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.5992 - acc: 0.6523Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6042 - acc: 0.6519 - val_loss: 6.9030 - val_acc: 0.5102
Epoch 35/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6342 - acc: 0.6498Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6031 - acc: 0.6518 - val_loss: 6.8711 - val_acc: 0.5054
Epoch 36/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.5934 - acc: 0.6526Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8646 - val_acc: 0.5198
Epoch 37/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5769 - acc: 0.6535Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8826 - val_acc: 0.5078
Epoch 38/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6001 - acc: 0.6523Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6003 - acc: 0.6522 - val_loss: 6.8627 - val_acc: 0.5102
Epoch 39/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6200 - acc: 0.6511Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6063 - acc: 0.6518 - val_loss: 6.8709 - val_acc: 0.5162
Epoch 40/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6517Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8543 - val_acc: 0.5162
Epoch 41/50
6460/6680 [============================>.] - ETA: 0s - loss: 5.6184 - acc: 0.6506Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6047 - acc: 0.6515 - val_loss: 6.8579 - val_acc: 0.5126
Epoch 42/50
6640/6680 [============================>.] - ETA: 0s - loss: 5.6153 - acc: 0.6512Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6034 - acc: 0.6519 - val_loss: 6.8870 - val_acc: 0.5054
Epoch 43/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6521Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6045 - acc: 0.6521 - val_loss: 6.8622 - val_acc: 0.5138
Epoch 44/50
6540/6680 [============================>.] - ETA: 0s - loss: 5.6018 - acc: 0.6520Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 2s 250us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8974 - val_acc: 0.5066
Epoch 45/50
6440/6680 [===========================>..] - ETA: 0s - loss: 5.5969 - acc: 0.6525Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6034 - acc: 0.6521 - val_loss: 6.8866 - val_acc: 0.5018
Epoch 46/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.5850 - acc: 0.6531Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 2s 253us/step - loss: 5.6036 - acc: 0.6519 - val_loss: 6.8485 - val_acc: 0.5102
Epoch 47/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6030 - acc: 0.6518Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6060 - acc: 0.6516 - val_loss: 6.8473 - val_acc: 0.5138
Epoch 48/50
6640/6680 [============================>.] - ETA: 0s - loss: 5.6035 - acc: 0.6520Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 2s 252us/step - loss: 5.6062 - acc: 0.6518 - val_loss: 6.8772 - val_acc: 0.5114
Epoch 49/50
6500/6680 [============================>.] - ETA: 0s - loss: 5.5894 - acc: 0.6529Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 2s 251us/step - loss: 5.6044 - acc: 0.6519 - val_loss: 6.9241 - val_acc: 0.5138
Epoch 50/50
6640/6680 [============================>.] - ETA: 0s - loss: 5.5952 - acc: 0.6524Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 2s 253us/step - loss: 5.6027 - acc: 0.6519 - val_loss: 6.8733 - val_acc: 0.5090

Batch size=35 Epoch=20
Train on 6680 samples, validate on 835 samples
Epoch 1/20
6545/6680 [============================>.] - ETA: 0s - loss: 5.5901 - acc: 0.6526Epoch 00001: val_loss improved from inf to 6.87290, saving model to saved_models1/weights.best.vgg16_bs35_ep20.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8729 - val_acc: 0.5078
Epoch 2/20
6370/6680 [===========================>..] - ETA: 0s - loss: 5.5953 - acc: 0.6523Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8882 - val_acc: 0.5138
Epoch 3/20
6370/6680 [===========================>..] - ETA: 0s - loss: 5.6127 - acc: 0.6512Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8785 - val_acc: 0.5042
Epoch 4/20
6615/6680 [============================>.] - ETA: 0s - loss: 5.6223 - acc: 0.6508Epoch 00004: val_loss improved from 6.87290 to 6.85918, saving model to saved_models1/weights.best.vgg16_bs35_ep20.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8592 - val_acc: 0.5078
Epoch 5/20
6545/6680 [============================>.] - ETA: 0s - loss: 5.5898 - acc: 0.6529Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6071 - acc: 0.6518 - val_loss: 6.8654 - val_acc: 0.5090
Epoch 6/20
6405/6680 [===========================>..] - ETA: 0s - loss: 5.5723 - acc: 0.6539Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6059 - acc: 0.6518 - val_loss: 6.8818 - val_acc: 0.5090
Epoch 7/20
6615/6680 [============================>.] - ETA: 0s - loss: 5.6120 - acc: 0.6512Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8714 - val_acc: 0.5042
Epoch 8/20
6510/6680 [============================>.] - ETA: 0s - loss: 5.6189 - acc: 0.6508Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6062 - acc: 0.6516 - val_loss: 6.8600 - val_acc: 0.5090
Epoch 9/20
6580/6680 [============================>.] - ETA: 0s - loss: 5.6097 - acc: 0.6514Epoch 00009: val_loss improved from 6.85918 to 6.83809, saving model to saved_models1/weights.best.vgg16_bs35_ep20.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6029 - acc: 0.6518 - val_loss: 6.8381 - val_acc: 0.5078
Epoch 10/20
6650/6680 [============================>.] - ETA: 0s - loss: 5.6009 - acc: 0.6522Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.9139 - val_acc: 0.5042
Epoch 11/20
6510/6680 [============================>.] - ETA: 0s - loss: 5.6332 - acc: 0.6501Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.8590 - val_acc: 0.5162
Epoch 12/20
6580/6680 [============================>.] - ETA: 0s - loss: 5.6105 - acc: 0.6511Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6062 - acc: 0.6513 - val_loss: 6.8521 - val_acc: 0.5114
Epoch 13/20
6510/6680 [============================>.] - ETA: 0s - loss: 5.6302 - acc: 0.6504Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8982 - val_acc: 0.5066
Epoch 14/20
6615/6680 [============================>.] - ETA: 0s - loss: 5.6012 - acc: 0.6522Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8895 - val_acc: 0.5078
Epoch 15/20
6580/6680 [============================>.] - ETA: 0s - loss: 5.5961 - acc: 0.6521Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6041 - acc: 0.6516 - val_loss: 6.8623 - val_acc: 0.5126
Epoch 16/20
6580/6680 [============================>.] - ETA: 0s - loss: 5.6100 - acc: 0.6517Epoch 00016: val_loss improved from 6.83809 to 6.83095, saving model to saved_models1/weights.best.vgg16_bs35_ep20.hdf5
6680/6680 [==============================] - 1s 173us/step - loss: 5.6032 - acc: 0.6521 - val_loss: 6.8310 - val_acc: 0.5114
Epoch 17/20
6580/6680 [============================>.] - ETA: 0s - loss: 5.5967 - acc: 0.6523Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8367 - val_acc: 0.5114
Epoch 18/20
6615/6680 [============================>.] - ETA: 0s - loss: 5.6159 - acc: 0.6509Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6516 - val_loss: 6.8710 - val_acc: 0.5066
Epoch 19/20
6650/6680 [============================>.] - ETA: 0s - loss: 5.6063 - acc: 0.6519Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6029 - acc: 0.6521 - val_loss: 6.8551 - val_acc: 0.5102
Epoch 20/20
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6001 - acc: 0.6520Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6040 - acc: 0.6518 - val_loss: 6.8704 - val_acc: 0.5126

Batch size=35 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6030 - acc: 0.6519Epoch 00001: val_loss improved from inf to 6.86478, saving model to saved_models1/weights.best.vgg16_bs35_ep35.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6032 - acc: 0.6519 - val_loss: 6.8648 - val_acc: 0.5054
Epoch 2/35
6615/6680 [============================>.] - ETA: 0s - loss: 5.5987 - acc: 0.6522Epoch 00002: val_loss improved from 6.86478 to 6.82769, saving model to saved_models1/weights.best.vgg16_bs35_ep35.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8277 - val_acc: 0.5162
Epoch 3/35
6650/6680 [============================>.] - ETA: 0s - loss: 5.5999 - acc: 0.6520Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6061 - acc: 0.6516 - val_loss: 6.8400 - val_acc: 0.5042
Epoch 4/35
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6159 - acc: 0.6511Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8558 - val_acc: 0.5078
Epoch 5/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6015 - acc: 0.6521Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8625 - val_acc: 0.5018
Epoch 6/35
6440/6680 [===========================>..] - ETA: 0s - loss: 5.5929 - acc: 0.6526Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6042 - acc: 0.6519 - val_loss: 6.8489 - val_acc: 0.5114
Epoch 7/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.6062 - acc: 0.6518Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6035 - acc: 0.6519 - val_loss: 6.8747 - val_acc: 0.5114
Epoch 8/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.6144 - acc: 0.6511Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6027 - acc: 0.6518 - val_loss: 6.8634 - val_acc: 0.5150
Epoch 9/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.6312 - acc: 0.6502Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8810 - val_acc: 0.5102
Epoch 10/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.5876 - acc: 0.6528Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8562 - val_acc: 0.5126
Epoch 11/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.5930 - acc: 0.6525Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6050 - acc: 0.6518 - val_loss: 6.8600 - val_acc: 0.5114
Epoch 12/35
6615/6680 [============================>.] - ETA: 0s - loss: 5.6195 - acc: 0.6511Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6058 - acc: 0.6519 - val_loss: 6.9067 - val_acc: 0.5078
Epoch 13/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.6026 - acc: 0.6518Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8904 - val_acc: 0.5090
Epoch 14/35
6335/6680 [===========================>..] - ETA: 0s - loss: 5.6106 - acc: 0.6515Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6058 - acc: 0.6516 - val_loss: 6.8788 - val_acc: 0.5114
Epoch 15/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6226 - acc: 0.6504Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6055 - acc: 0.6515 - val_loss: 6.8786 - val_acc: 0.5054
Epoch 16/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.5861 - acc: 0.6530Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6035 - acc: 0.6519 - val_loss: 6.8733 - val_acc: 0.5090
Epoch 17/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6031 - acc: 0.6515Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6033 - acc: 0.6515 - val_loss: 6.8490 - val_acc: 0.5114
Epoch 18/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.6089 - acc: 0.6515Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8579 - val_acc: 0.5114
Epoch 19/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.5955 - acc: 0.6522Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6051 - acc: 0.6516 - val_loss: 6.8765 - val_acc: 0.5042
Epoch 20/35
6405/6680 [===========================>..] - ETA: 0s - loss: 5.5843 - acc: 0.6528Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8854 - val_acc: 0.5078
Epoch 21/35
6440/6680 [===========================>..] - ETA: 0s - loss: 5.5922 - acc: 0.6526Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6036 - acc: 0.6519 - val_loss: 6.8616 - val_acc: 0.5030
Epoch 22/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.6065 - acc: 0.6518Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8547 - val_acc: 0.5126
Epoch 23/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.5945 - acc: 0.6524Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6041 - acc: 0.6518 - val_loss: 6.8560 - val_acc: 0.5126
Epoch 24/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6247 - acc: 0.6507Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8705 - val_acc: 0.5114
Epoch 25/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.5956 - acc: 0.6524Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 173us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8385 - val_acc: 0.5090
Epoch 26/35
6475/6680 [============================>.] - ETA: 0s - loss: 5.6052 - acc: 0.6517Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8809 - val_acc: 0.5078
Epoch 27/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.5929 - acc: 0.6526Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6057 - acc: 0.6518 - val_loss: 6.8526 - val_acc: 0.5090
Epoch 28/35
6545/6680 [============================>.] - ETA: 0s - loss: 5.6195 - acc: 0.6510Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6049 - acc: 0.6519 - val_loss: 6.8894 - val_acc: 0.5042
Epoch 29/35
6650/6680 [============================>.] - ETA: 0s - loss: 5.6041 - acc: 0.6520Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6055 - acc: 0.6519 - val_loss: 6.8577 - val_acc: 0.5090
Epoch 30/35
6475/6680 [============================>.] - ETA: 0s - loss: 5.6025 - acc: 0.6519Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8665 - val_acc: 0.5102
Epoch 31/35
6475/6680 [============================>.] - ETA: 0s - loss: 5.6162 - acc: 0.6511Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8533 - val_acc: 0.5114
Epoch 32/35
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6124 - acc: 0.6511Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6038 - acc: 0.6516 - val_loss: 6.8764 - val_acc: 0.5102
Epoch 33/35
6510/6680 [============================>.] - ETA: 0s - loss: 5.6315 - acc: 0.6499Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6056 - acc: 0.6515 - val_loss: 6.8899 - val_acc: 0.5066
Epoch 34/35
6580/6680 [============================>.] - ETA: 0s - loss: 5.6080 - acc: 0.6518Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6037 - acc: 0.6521 - val_loss: 6.9018 - val_acc: 0.5054
Epoch 35/35
6650/6680 [============================>.] - ETA: 0s - loss: 5.5985 - acc: 0.6523Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8915 - val_acc: 0.5042

Batch size=35 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.5962 - acc: 0.6523Epoch 00001: val_loss improved from inf to 6.83195, saving model to saved_models1/weights.best.vgg16_bs35_ep40.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.8320 - val_acc: 0.5126
Epoch 2/40
6510/6680 [============================>.] - ETA: 0s - loss: 5.5891 - acc: 0.6528Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8679 - val_acc: 0.5114
Epoch 3/40
6335/6680 [===========================>..] - ETA: 0s - loss: 5.6187 - acc: 0.6508Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6043 - acc: 0.6516 - val_loss: 6.8734 - val_acc: 0.5054
Epoch 4/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6007 - acc: 0.6519Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8666 - val_acc: 0.5126
Epoch 5/40
6580/6680 [============================>.] - ETA: 0s - loss: 5.5982 - acc: 0.6520Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6037 - acc: 0.6516 - val_loss: 6.8424 - val_acc: 0.5090
Epoch 6/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6017 - acc: 0.6518Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6044 - acc: 0.6516 - val_loss: 6.8726 - val_acc: 0.5078
Epoch 7/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.6007 - acc: 0.6519Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 173us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8436 - val_acc: 0.5162
Epoch 8/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.6102 - acc: 0.6514Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8575 - val_acc: 0.5186
Epoch 9/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.5930 - acc: 0.6523Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6041 - acc: 0.6516 - val_loss: 6.8621 - val_acc: 0.5126
Epoch 10/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6014 - acc: 0.6519Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6041 - acc: 0.6518 - val_loss: 6.9093 - val_acc: 0.5126
Epoch 11/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6129 - acc: 0.6510Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6057 - acc: 0.6515 - val_loss: 6.8724 - val_acc: 0.5138
Epoch 12/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6010 - acc: 0.6522Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6020 - acc: 0.6521 - val_loss: 6.8571 - val_acc: 0.5150
Epoch 13/40
6510/6680 [============================>.] - ETA: 0s - loss: 5.5847 - acc: 0.6533Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6042 - acc: 0.6521 - val_loss: 6.8704 - val_acc: 0.5126
Epoch 14/40
6580/6680 [============================>.] - ETA: 0s - loss: 5.5992 - acc: 0.6523Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6060 - acc: 0.6518 - val_loss: 6.8789 - val_acc: 0.5054
Epoch 15/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6169 - acc: 0.6511Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6062 - acc: 0.6518 - val_loss: 6.8822 - val_acc: 0.5138
Epoch 16/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.5953 - acc: 0.6523Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 177us/step - loss: 5.6060 - acc: 0.6516 - val_loss: 6.8861 - val_acc: 0.5066
Epoch 17/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6090 - acc: 0.6515Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.9073 - val_acc: 0.5090
Epoch 18/40
6580/6680 [============================>.] - ETA: 0s - loss: 5.6050 - acc: 0.6515Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6055 - acc: 0.6515 - val_loss: 6.8782 - val_acc: 0.5102
Epoch 19/40
6510/6680 [============================>.] - ETA: 0s - loss: 5.6112 - acc: 0.6513Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6515 - val_loss: 6.8843 - val_acc: 0.5114
Epoch 20/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6228 - acc: 0.6506Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6033 - acc: 0.6518 - val_loss: 6.8778 - val_acc: 0.5114
Epoch 21/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.5936 - acc: 0.6522Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8788 - val_acc: 0.5042
Epoch 22/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.5881 - acc: 0.6527Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6048 - acc: 0.6516 - val_loss: 6.8894 - val_acc: 0.5102
Epoch 23/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6037 - acc: 0.6517Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6051 - acc: 0.6516 - val_loss: 6.8899 - val_acc: 0.5006
Epoch 24/40
6580/6680 [============================>.] - ETA: 0s - loss: 5.5978 - acc: 0.6524Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6519 - val_loss: 6.8857 - val_acc: 0.5114
Epoch 25/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.5926 - acc: 0.6527Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8383 - val_acc: 0.5138
Epoch 26/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6116 - acc: 0.6513Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8608 - val_acc: 0.5114
Epoch 27/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6150 - acc: 0.6511Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8719 - val_acc: 0.5114
Epoch 28/40
6510/6680 [============================>.] - ETA: 0s - loss: 5.5822 - acc: 0.6531Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8608 - val_acc: 0.5114
Epoch 29/40
6440/6680 [===========================>..] - ETA: 0s - loss: 5.5874 - acc: 0.6530Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8476 - val_acc: 0.5126
Epoch 30/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6186 - acc: 0.6510Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6055 - acc: 0.6518 - val_loss: 6.8617 - val_acc: 0.5186
Epoch 31/40
6335/6680 [===========================>..] - ETA: 0s - loss: 5.5899 - acc: 0.6526Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6052 - acc: 0.6516 - val_loss: 6.8579 - val_acc: 0.5114
Epoch 32/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6110 - acc: 0.6514Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8823 - val_acc: 0.5066
Epoch 33/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6091 - acc: 0.6514Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8773 - val_acc: 0.5102
Epoch 34/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.6004 - acc: 0.6520Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8858 - val_acc: 0.5102
Epoch 35/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6186 - acc: 0.6509Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.8673 - val_acc: 0.5066
Epoch 36/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6047 - acc: 0.6519Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6057 - acc: 0.6518 - val_loss: 6.8521 - val_acc: 0.5090
Epoch 37/40
6650/6680 [============================>.] - ETA: 0s - loss: 5.6090 - acc: 0.6516Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6031 - acc: 0.6519 - val_loss: 6.8998 - val_acc: 0.5030
Epoch 38/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6020 - acc: 0.6517Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6054 - acc: 0.6515 - val_loss: 6.8954 - val_acc: 0.5078
Epoch 39/40
6615/6680 [============================>.] - ETA: 0s - loss: 5.6110 - acc: 0.6512Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8740 - val_acc: 0.5114
Epoch 40/40
6545/6680 [============================>.] - ETA: 0s - loss: 5.6206 - acc: 0.6509Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6036 - acc: 0.6519 - val_loss: 6.9101 - val_acc: 0.5102

Batch size=35 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.5983 - acc: 0.6519Epoch 00001: val_loss improved from inf to 6.84077, saving model to saved_models1/weights.best.vgg16_bs35_ep50.hdf5
6680/6680 [==============================] - 1s 173us/step - loss: 5.6058 - acc: 0.6515 - val_loss: 6.8408 - val_acc: 0.5162
Epoch 2/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.5869 - acc: 0.6530Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6019 - acc: 0.6521 - val_loss: 6.8734 - val_acc: 0.5090
Epoch 3/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6049 - acc: 0.6519Epoch 00003: val_loss improved from 6.84077 to 6.80713, saving model to saved_models1/weights.best.vgg16_bs35_ep50.hdf5
6680/6680 [==============================] - 1s 171us/step - loss: 5.6034 - acc: 0.6519 - val_loss: 6.8071 - val_acc: 0.5198
Epoch 4/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.5968 - acc: 0.6526Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6521 - val_loss: 6.8701 - val_acc: 0.5090
Epoch 5/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.5967 - acc: 0.6523Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8701 - val_acc: 0.5126
Epoch 6/50
6335/6680 [===========================>..] - ETA: 0s - loss: 5.5780 - acc: 0.6537Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6036 - acc: 0.6521 - val_loss: 6.8549 - val_acc: 0.5114
Epoch 7/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6039 - acc: 0.6521Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6037 - acc: 0.6521 - val_loss: 6.8582 - val_acc: 0.5114
Epoch 8/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.6049 - acc: 0.6519Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8512 - val_acc: 0.5114
Epoch 9/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.5948 - acc: 0.6523Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8795 - val_acc: 0.5102
Epoch 10/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6023 - acc: 0.6517Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6515 - val_loss: 6.8896 - val_acc: 0.5078
Epoch 11/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.5976 - acc: 0.6522Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6038 - acc: 0.6518 - val_loss: 6.8690 - val_acc: 0.5030
Epoch 12/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.5942 - acc: 0.6524Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8813 - val_acc: 0.5090
Epoch 13/50
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6264 - acc: 0.6506Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6052 - acc: 0.6519 - val_loss: 6.8874 - val_acc: 0.5114
Epoch 14/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6155 - acc: 0.6513Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 172us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8736 - val_acc: 0.5066
Epoch 15/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6104 - acc: 0.6515Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6060 - acc: 0.6518 - val_loss: 6.8661 - val_acc: 0.5126
Epoch 16/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.6011 - acc: 0.6523Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6038 - acc: 0.6521 - val_loss: 6.9027 - val_acc: 0.5030
Epoch 17/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6168 - acc: 0.6508Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6056 - acc: 0.6515 - val_loss: 6.9067 - val_acc: 0.5018
Epoch 18/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.5949 - acc: 0.6525Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6032 - acc: 0.6519 - val_loss: 6.8699 - val_acc: 0.5078
Epoch 19/50
6475/6680 [============================>.] - ETA: 0s - loss: 5.5707 - acc: 0.6541Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6024 - acc: 0.6521 - val_loss: 6.9001 - val_acc: 0.5078
Epoch 20/50
6335/6680 [===========================>..] - ETA: 0s - loss: 5.6186 - acc: 0.6511Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6034 - acc: 0.6521 - val_loss: 6.8629 - val_acc: 0.5054
Epoch 21/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6109 - acc: 0.6512Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8854 - val_acc: 0.5054
Epoch 22/50
6440/6680 [===========================>..] - ETA: 0s - loss: 5.5993 - acc: 0.6519Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6056 - acc: 0.6515 - val_loss: 6.8920 - val_acc: 0.5078
Epoch 23/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.5926 - acc: 0.6526Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.9049 - val_acc: 0.5054
Epoch 24/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.5950 - acc: 0.6524Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6030 - acc: 0.6519 - val_loss: 6.8917 - val_acc: 0.5030
Epoch 25/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.6312 - acc: 0.6501Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8598 - val_acc: 0.5138
Epoch 26/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.6091 - acc: 0.6513Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6056 - acc: 0.6515 - val_loss: 6.8613 - val_acc: 0.5102
Epoch 27/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.5894 - acc: 0.6527Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8220 - val_acc: 0.5138
Epoch 28/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.6028 - acc: 0.6519Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8744 - val_acc: 0.5054
Epoch 29/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6110 - acc: 0.6512Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6042 - acc: 0.6516 - val_loss: 6.8616 - val_acc: 0.5126
Epoch 30/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6024 - acc: 0.6519Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8862 - val_acc: 0.5090
Epoch 31/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.6036 - acc: 0.6519Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.9106 - val_acc: 0.5054
Epoch 32/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6059 - acc: 0.6516Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6032 - acc: 0.6518 - val_loss: 6.9040 - val_acc: 0.5006
Epoch 33/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.5877 - acc: 0.6529Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6027 - acc: 0.6519 - val_loss: 6.8928 - val_acc: 0.5078
Epoch 34/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6187 - acc: 0.6508Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6036 - acc: 0.6518 - val_loss: 6.8671 - val_acc: 0.5138
Epoch 35/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6139 - acc: 0.6509Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6515 - val_loss: 6.8647 - val_acc: 0.5090
Epoch 36/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6071 - acc: 0.6515Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6044 - acc: 0.6516 - val_loss: 6.8632 - val_acc: 0.5102
Epoch 37/50
6475/6680 [============================>.] - ETA: 0s - loss: 5.5964 - acc: 0.6525Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6057 - acc: 0.6519 - val_loss: 6.8559 - val_acc: 0.5114
Epoch 38/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6329 - acc: 0.6500Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6041 - acc: 0.6518 - val_loss: 6.8995 - val_acc: 0.5030
Epoch 39/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.6146 - acc: 0.6511Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6034 - acc: 0.6518 - val_loss: 6.8703 - val_acc: 0.5126
Epoch 40/50
6475/6680 [============================>.] - ETA: 0s - loss: 5.6194 - acc: 0.6510Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8981 - val_acc: 0.5078
Epoch 41/50
6335/6680 [===========================>..] - ETA: 0s - loss: 5.5844 - acc: 0.6530Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 173us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.8701 - val_acc: 0.5066
Epoch 42/50
6650/6680 [============================>.] - ETA: 0s - loss: 5.6058 - acc: 0.6516Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6048 - acc: 0.6516 - val_loss: 6.8773 - val_acc: 0.5054
Epoch 43/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.5791 - acc: 0.6534Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6044 - acc: 0.6518 - val_loss: 6.8529 - val_acc: 0.5138
Epoch 44/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.6259 - acc: 0.6504Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6039 - acc: 0.6518 - val_loss: 6.8792 - val_acc: 0.5102
Epoch 45/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6362 - acc: 0.6499Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8703 - val_acc: 0.5090
Epoch 46/50
6335/6680 [===========================>..] - ETA: 0s - loss: 5.6120 - acc: 0.6513Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8932 - val_acc: 0.5018
Epoch 47/50
6580/6680 [============================>.] - ETA: 0s - loss: 5.6138 - acc: 0.6515Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6029 - acc: 0.6521 - val_loss: 6.8562 - val_acc: 0.5126
Epoch 48/50
6615/6680 [============================>.] - ETA: 0s - loss: 5.5972 - acc: 0.6522Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6031 - acc: 0.6518 - val_loss: 6.8408 - val_acc: 0.5126
Epoch 49/50
6510/6680 [============================>.] - ETA: 0s - loss: 5.6212 - acc: 0.6507Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6036 - acc: 0.6518 - val_loss: 6.8382 - val_acc: 0.5150
Epoch 50/50
6545/6680 [============================>.] - ETA: 0s - loss: 5.6010 - acc: 0.6523Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6021 - acc: 0.6521 - val_loss: 6.8866 - val_acc: 0.5066

Batch size=37 Epoch=20
Train on 6680 samples, validate on 835 samples
Epoch 1/20
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6079 - acc: 0.6515Epoch 00001: val_loss improved from inf to 6.85845, saving model to saved_models1/weights.best.vgg16_bs37_ep20.hdf5
6680/6680 [==============================] - 1s 168us/step - loss: 5.6054 - acc: 0.6516 - val_loss: 6.8584 - val_acc: 0.5078
Epoch 2/20
6623/6680 [============================>.] - ETA: 0s - loss: 5.6197 - acc: 0.6511Epoch 00002: val_loss improved from 6.85845 to 6.85738, saving model to saved_models1/weights.best.vgg16_bs37_ep20.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6056 - acc: 0.6519 - val_loss: 6.8574 - val_acc: 0.5138
Epoch 3/20
6660/6680 [============================>.] - ETA: 0s - loss: 5.6088 - acc: 0.6515Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6041 - acc: 0.6518 - val_loss: 6.8861 - val_acc: 0.5126
Epoch 4/20
6586/6680 [============================>.] - ETA: 0s - loss: 5.5898 - acc: 0.6527Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6037 - acc: 0.6518 - val_loss: 6.8618 - val_acc: 0.5138
Epoch 5/20
6512/6680 [============================>.] - ETA: 0s - loss: 5.6025 - acc: 0.6522Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6034 - acc: 0.6521 - val_loss: 6.8938 - val_acc: 0.5042
Epoch 6/20
6586/6680 [============================>.] - ETA: 0s - loss: 5.5996 - acc: 0.6521Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6040 - acc: 0.6518 - val_loss: 6.8888 - val_acc: 0.5102
Epoch 7/20
6549/6680 [============================>.] - ETA: 0s - loss: 5.5648 - acc: 0.6543Epoch 00007: val_loss improved from 6.85738 to 6.85246, saving model to saved_models1/weights.best.vgg16_bs37_ep20.hdf5
6680/6680 [==============================] - 1s 168us/step - loss: 5.6029 - acc: 0.6519 - val_loss: 6.8525 - val_acc: 0.5126
Epoch 8/20
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6037 - acc: 0.6518Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6024 - acc: 0.6518 - val_loss: 6.9009 - val_acc: 0.5066
Epoch 9/20
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6001 - acc: 0.6519Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6048 - acc: 0.6516 - val_loss: 6.8913 - val_acc: 0.5042
Epoch 10/20
6623/6680 [============================>.] - ETA: 0s - loss: 5.5961 - acc: 0.6524Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6014 - acc: 0.6521 - val_loss: 6.9158 - val_acc: 0.5078
Epoch 11/20
6660/6680 [============================>.] - ETA: 0s - loss: 5.6017 - acc: 0.6520Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8586 - val_acc: 0.5162
Epoch 12/20
6660/6680 [============================>.] - ETA: 0s - loss: 5.5972 - acc: 0.6523Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6022 - acc: 0.6519 - val_loss: 6.8978 - val_acc: 0.5114
Epoch 13/20
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6124 - acc: 0.6515Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6059 - acc: 0.6518 - val_loss: 6.8885 - val_acc: 0.5102
Epoch 14/20
6660/6680 [============================>.] - ETA: 0s - loss: 5.6026 - acc: 0.6523Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6051 - acc: 0.6521 - val_loss: 6.8668 - val_acc: 0.5126
Epoch 15/20
6512/6680 [============================>.] - ETA: 0s - loss: 5.6268 - acc: 0.6506Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6060 - acc: 0.6519 - val_loss: 6.8647 - val_acc: 0.5066
Epoch 16/20
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5849 - acc: 0.6533Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6050 - acc: 0.6521 - val_loss: 6.8759 - val_acc: 0.5114
Epoch 17/20
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6038 - acc: 0.6518Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6058 - acc: 0.6516 - val_loss: 6.8585 - val_acc: 0.5150
Epoch 18/20
6549/6680 [============================>.] - ETA: 0s - loss: 5.6468 - acc: 0.6493Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6060 - acc: 0.6518 - val_loss: 6.8546 - val_acc: 0.5138
Epoch 19/20
6327/6680 [===========================>..] - ETA: 0s - loss: 5.5680 - acc: 0.6540Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8596 - val_acc: 0.5090
Epoch 20/20
6549/6680 [============================>.] - ETA: 0s - loss: 5.5890 - acc: 0.6529Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6025 - acc: 0.6521 - val_loss: 6.8708 - val_acc: 0.5138

Batch size=37 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6623/6680 [============================>.] - ETA: 0s - loss: 5.5991 - acc: 0.6520Epoch 00001: val_loss improved from inf to 6.88616, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6044 - acc: 0.6516 - val_loss: 6.8862 - val_acc: 0.5030
Epoch 2/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.6101 - acc: 0.6517Epoch 00002: val_loss improved from 6.88616 to 6.86639, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6053 - acc: 0.6519 - val_loss: 6.8664 - val_acc: 0.5018
Epoch 3/35
6623/6680 [============================>.] - ETA: 0s - loss: 5.6047 - acc: 0.6518Epoch 00003: val_loss improved from 6.86639 to 6.85749, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8575 - val_acc: 0.5150
Epoch 4/35
6512/6680 [============================>.] - ETA: 0s - loss: 5.6114 - acc: 0.6514Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6054 - acc: 0.6518 - val_loss: 6.8742 - val_acc: 0.5114
Epoch 5/35
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6308 - acc: 0.6502Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8755 - val_acc: 0.5078
Epoch 6/35
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6056 - acc: 0.6520Epoch 00006: val_loss improved from 6.85749 to 6.85091, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6038 - acc: 0.6521 - val_loss: 6.8509 - val_acc: 0.5126
Epoch 7/35
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5831 - acc: 0.6530Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6033 - acc: 0.6518 - val_loss: 6.8586 - val_acc: 0.5090
Epoch 8/35
6327/6680 [===========================>..] - ETA: 0s - loss: 5.5835 - acc: 0.6532Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6045 - acc: 0.6519 - val_loss: 6.8597 - val_acc: 0.5138
Epoch 9/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.6036 - acc: 0.6520Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6062 - acc: 0.6518 - val_loss: 6.8703 - val_acc: 0.5162
Epoch 10/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.6007 - acc: 0.6521Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6057 - acc: 0.6518 - val_loss: 6.8859 - val_acc: 0.5174
Epoch 11/35
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6065 - acc: 0.6516Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6040 - acc: 0.6518 - val_loss: 6.8935 - val_acc: 0.5090
Epoch 12/35
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6238 - acc: 0.6505Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6061 - acc: 0.6516 - val_loss: 6.8840 - val_acc: 0.5090
Epoch 13/35
6475/6680 [============================>.] - ETA: 0s - loss: 5.5929 - acc: 0.6525Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6060 - acc: 0.6516 - val_loss: 6.8684 - val_acc: 0.5126
Epoch 14/35
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6196 - acc: 0.6507Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6045 - acc: 0.6516 - val_loss: 6.8918 - val_acc: 0.5090
Epoch 15/35
6438/6680 [===========================>..] - ETA: 0s - loss: 5.5948 - acc: 0.6524Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 168us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8964 - val_acc: 0.5114
Epoch 16/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6148 - acc: 0.6508Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6050 - acc: 0.6515 - val_loss: 6.8777 - val_acc: 0.5078
Epoch 17/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5660 - acc: 0.6540Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6043 - acc: 0.6515 - val_loss: 6.8608 - val_acc: 0.5150
Epoch 18/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5882 - acc: 0.6526Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6038 - acc: 0.6516 - val_loss: 6.8510 - val_acc: 0.5102
Epoch 19/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5801 - acc: 0.6532Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8669 - val_acc: 0.5174
Epoch 20/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6337 - acc: 0.6499Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6049 - acc: 0.6516 - val_loss: 6.8805 - val_acc: 0.5138
Epoch 21/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6012 - acc: 0.6519Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6040 - acc: 0.6518 - val_loss: 6.9037 - val_acc: 0.5102
Epoch 22/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6178 - acc: 0.6508Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6030 - acc: 0.6518 - val_loss: 6.8594 - val_acc: 0.5054
Epoch 23/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6076 - acc: 0.6515Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8924 - val_acc: 0.5078
Epoch 24/35
6475/6680 [============================>.] - ETA: 0s - loss: 5.5788 - acc: 0.6536Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6055 - acc: 0.6519 - val_loss: 6.8872 - val_acc: 0.5066
Epoch 25/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5878 - acc: 0.6527Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6058 - acc: 0.6516 - val_loss: 6.8577 - val_acc: 0.5114
Epoch 26/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6017 - acc: 0.6519Epoch 00026: val_loss improved from 6.85091 to 6.84878, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 172us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8488 - val_acc: 0.5138
Epoch 27/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6078 - acc: 0.6518Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8853 - val_acc: 0.5102
Epoch 28/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6173 - acc: 0.6510Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6049 - acc: 0.6518 - val_loss: 6.8555 - val_acc: 0.5126
Epoch 29/35
6586/6680 [============================>.] - ETA: 0s - loss: 5.6138 - acc: 0.6512Epoch 00029: val_loss improved from 6.84878 to 6.83731, saving model to saved_models1/weights.best.vgg16_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 168us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8373 - val_acc: 0.5126
Epoch 30/35
6549/6680 [============================>.] - ETA: 0s - loss: 5.6461 - acc: 0.6494Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6053 - acc: 0.6519 - val_loss: 6.8802 - val_acc: 0.5138
Epoch 31/35
6660/6680 [============================>.] - ETA: 0s - loss: 5.6130 - acc: 0.6511Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6034 - acc: 0.6516 - val_loss: 6.8619 - val_acc: 0.5150
Epoch 32/35
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5922 - acc: 0.6527Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6026 - acc: 0.6519 - val_loss: 6.8670 - val_acc: 0.5102
Epoch 33/35
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6242 - acc: 0.6507- ETA: 0s - loss: 5.9Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8584 - val_acc: 0.5102
Epoch 34/35
6623/6680 [============================>.] - ETA: 0s - loss: 5.6144 - acc: 0.6514Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8816 - val_acc: 0.5102
Epoch 35/35
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6143 - acc: 0.6512Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8800 - val_acc: 0.5090

Batch size=37 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6549/6680 [============================>.] - ETA: 0s - loss: 5.6262 - acc: 0.6505Epoch 00001: val_loss improved from inf to 6.86902, saving model to saved_models1/weights.best.vgg16_bs37_ep40.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8690 - val_acc: 0.5090
Epoch 2/40
6586/6680 [============================>.] - ETA: 0s - loss: 5.5878 - acc: 0.6526Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6033 - acc: 0.6516 - val_loss: 6.8778 - val_acc: 0.5066
Epoch 3/40
6512/6680 [============================>.] - ETA: 0s - loss: 5.6036 - acc: 0.6520Epoch 00003: val_loss improved from 6.86902 to 6.85879, saving model to saved_models1/weights.best.vgg16_bs37_ep40.hdf5
6680/6680 [==============================] - 1s 165us/step - loss: 5.6050 - acc: 0.6519 - val_loss: 6.8588 - val_acc: 0.5090
Epoch 4/40
6549/6680 [============================>.] - ETA: 0s - loss: 5.6121 - acc: 0.6512Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6058 - acc: 0.6516 - val_loss: 6.8614 - val_acc: 0.5102
Epoch 5/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.5936 - acc: 0.6526Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8831 - val_acc: 0.5150
Epoch 6/40
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5918 - acc: 0.6526Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8850 - val_acc: 0.5102
Epoch 7/40
6549/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6519Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6054 - acc: 0.6518 - val_loss: 6.8754 - val_acc: 0.5090
Epoch 8/40
6549/6680 [============================>.] - ETA: 0s - loss: 5.5996 - acc: 0.6520Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8677 - val_acc: 0.5090
Epoch 9/40
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6084 - acc: 0.6516Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8745 - val_acc: 0.5042
Epoch 10/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.6022 - acc: 0.6523Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6048 - acc: 0.6521 - val_loss: 6.8702 - val_acc: 0.5042
Epoch 11/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.6027 - acc: 0.6518Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6028 - acc: 0.6518 - val_loss: 6.8911 - val_acc: 0.5114
Epoch 12/40
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5923 - acc: 0.6529Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8705 - val_acc: 0.5066
Epoch 13/40
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6217 - acc: 0.6505Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8815 - val_acc: 0.5042
Epoch 14/40
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6044 - acc: 0.6521Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6040 - acc: 0.6521 - val_loss: 6.8617 - val_acc: 0.5066
Epoch 15/40
6512/6680 [============================>.] - ETA: 0s - loss: 5.5942 - acc: 0.6525Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8820 - val_acc: 0.5030
Epoch 16/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.6108 - acc: 0.6514Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8703 - val_acc: 0.5054
Epoch 17/40
6549/6680 [============================>.] - ETA: 0s - loss: 5.5921 - acc: 0.6526Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6031 - acc: 0.6519 - val_loss: 6.8667 - val_acc: 0.5102
Epoch 18/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.6135 - acc: 0.6512Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8967 - val_acc: 0.5066
Epoch 19/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.6065 - acc: 0.6515Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6045 - acc: 0.6516 - val_loss: 6.9068 - val_acc: 0.5078
Epoch 20/40
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6082 - acc: 0.6516Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6058 - acc: 0.6516 - val_loss: 6.8955 - val_acc: 0.5066
Epoch 21/40
6327/6680 [===========================>..] - ETA: 0s - loss: 5.5984 - acc: 0.6524Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6049 - acc: 0.6519 - val_loss: 6.8763 - val_acc: 0.5114
Epoch 22/40
6586/6680 [============================>.] - ETA: 0s - loss: 5.6141 - acc: 0.6515Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6051 - acc: 0.6521 - val_loss: 6.8680 - val_acc: 0.5102
Epoch 23/40
6512/6680 [============================>.] - ETA: 0s - loss: 5.6054 - acc: 0.6519Epoch 00023: val_loss improved from 6.85879 to 6.85426, saving model to saved_models1/weights.best.vgg16_bs37_ep40.hdf5
6680/6680 [==============================] - 1s 165us/step - loss: 5.6044 - acc: 0.6519 - val_loss: 6.8543 - val_acc: 0.5102
Epoch 24/40
6586/6680 [============================>.] - ETA: 0s - loss: 5.6068 - acc: 0.6517Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8756 - val_acc: 0.5066
Epoch 25/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.5926 - acc: 0.6527Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6028 - acc: 0.6521 - val_loss: 6.8733 - val_acc: 0.5078
Epoch 26/40
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6261 - acc: 0.6504Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6047 - acc: 0.6516 - val_loss: 6.8621 - val_acc: 0.5078
Epoch 27/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.5989 - acc: 0.6520Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6018 - acc: 0.6518 - val_loss: 6.9102 - val_acc: 0.5042
Epoch 28/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.6165 - acc: 0.6511Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8637 - val_acc: 0.5114
Epoch 29/40
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6143 - acc: 0.6513Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6040 - acc: 0.6519 - val_loss: 6.8624 - val_acc: 0.5114
Epoch 30/40
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5868 - acc: 0.6530Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6048 - acc: 0.6519 - val_loss: 6.8784 - val_acc: 0.5102
Epoch 31/40
6623/6680 [============================>.] - ETA: 0s - loss: 5.6071 - acc: 0.6518Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6027 - acc: 0.6521 - val_loss: 6.8731 - val_acc: 0.5126
Epoch 32/40
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6342 - acc: 0.6498Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6516 - val_loss: 6.8693 - val_acc: 0.5150
Epoch 33/40
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6176 - acc: 0.6510Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6050 - acc: 0.6518 - val_loss: 6.8738 - val_acc: 0.5162
Epoch 34/40
6586/6680 [============================>.] - ETA: 0s - loss: 5.6064 - acc: 0.6517Epoch 00034: val_loss improved from 6.85426 to 6.84940, saving model to saved_models1/weights.best.vgg16_bs37_ep40.hdf5
6680/6680 [==============================] - 1s 167us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8494 - val_acc: 0.5150
Epoch 35/40
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6316 - acc: 0.6501Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6055 - acc: 0.6516 - val_loss: 6.8601 - val_acc: 0.5138
Epoch 36/40
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6036 - acc: 0.6521Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6036 - acc: 0.6521 - val_loss: 6.8944 - val_acc: 0.5102
Epoch 37/40
6475/6680 [============================>.] - ETA: 0s - loss: 5.6095 - acc: 0.6517Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6054 - acc: 0.6519 - val_loss: 6.8534 - val_acc: 0.5102
Epoch 38/40
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6184 - acc: 0.6508Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6036 - acc: 0.6518 - val_loss: 6.8541 - val_acc: 0.5126
Epoch 39/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.5942 - acc: 0.6523Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6040 - acc: 0.6516 - val_loss: 6.8654 - val_acc: 0.5162
Epoch 40/40
6660/6680 [============================>.] - ETA: 0s - loss: 5.6022 - acc: 0.6520Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8803 - val_acc: 0.5126

Batch size=37 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6017 - acc: 0.6518Epoch 00001: val_loss improved from inf to 6.87337, saving model to saved_models1/weights.best.vgg16_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6042 - acc: 0.6516 - val_loss: 6.8734 - val_acc: 0.5150
Epoch 2/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6047 - acc: 0.6518Epoch 00002: val_loss improved from 6.87337 to 6.85252, saving model to saved_models1/weights.best.vgg16_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 165us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8525 - val_acc: 0.5162
Epoch 3/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6059 - acc: 0.6517Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6036 - acc: 0.6518 - val_loss: 6.8638 - val_acc: 0.5174
Epoch 4/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.6168 - acc: 0.6509Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6056 - acc: 0.6516 - val_loss: 6.8542 - val_acc: 0.5162
Epoch 5/50
6475/6680 [============================>.] - ETA: 0s - loss: 5.5918 - acc: 0.6528Epoch 00005: val_loss improved from 6.85252 to 6.85111, saving model to saved_models1/weights.best.vgg16_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 165us/step - loss: 5.6060 - acc: 0.6519 - val_loss: 6.8511 - val_acc: 0.5150
Epoch 6/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6086 - acc: 0.6517Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6039 - acc: 0.6519 - val_loss: 6.8871 - val_acc: 0.5054
Epoch 7/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.6047 - acc: 0.6519Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6034 - acc: 0.6519 - val_loss: 6.8702 - val_acc: 0.5102
Epoch 8/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.6073 - acc: 0.6517Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6050 - acc: 0.6518 - val_loss: 6.8628 - val_acc: 0.5102
Epoch 9/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.6267 - acc: 0.6506Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6057 - acc: 0.6519 - val_loss: 6.8890 - val_acc: 0.5066
Epoch 10/50
6623/6680 [============================>.] - ETA: 0s - loss: 5.6135 - acc: 0.6512Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8743 - val_acc: 0.5102
Epoch 11/50
6364/6680 [===========================>..] - ETA: 0s - loss: 5.6305 - acc: 0.6501Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6030 - acc: 0.6518 - val_loss: 6.8518 - val_acc: 0.5126
Epoch 12/50
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6297 - acc: 0.6504Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6056 - acc: 0.6518 - val_loss: 6.8597 - val_acc: 0.5138
Epoch 13/50
6512/6680 [============================>.] - ETA: 0s - loss: 5.6051 - acc: 0.6517Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6041 - acc: 0.6518 - val_loss: 6.8617 - val_acc: 0.5066
Epoch 14/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.6092 - acc: 0.6518Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6051 - acc: 0.6521 - val_loss: 6.8586 - val_acc: 0.5102
Epoch 15/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5727 - acc: 0.6541Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8589 - val_acc: 0.5126
Epoch 16/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.5850 - acc: 0.6531Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6053 - acc: 0.6518 - val_loss: 6.8596 - val_acc: 0.5090
Epoch 17/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.5985 - acc: 0.6523Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6045 - acc: 0.6519 - val_loss: 6.8713 - val_acc: 0.5090
Epoch 18/50
6512/6680 [============================>.] - ETA: 0s - loss: 5.5891 - acc: 0.6525Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 162us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8699 - val_acc: 0.5138
Epoch 19/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6144 - acc: 0.6510Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6516 - val_loss: 6.8532 - val_acc: 0.5126
Epoch 20/50
6512/6680 [============================>.] - ETA: 0s - loss: 5.6025 - acc: 0.6520Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6040 - acc: 0.6519 - val_loss: 6.8656 - val_acc: 0.5090
Epoch 21/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5824 - acc: 0.6532Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6050 - acc: 0.6518 - val_loss: 6.8693 - val_acc: 0.5102
Epoch 22/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.5924 - acc: 0.6527Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8762 - val_acc: 0.5090
Epoch 23/50
6623/6680 [============================>.] - ETA: 0s - loss: 5.5996 - acc: 0.6518Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6049 - acc: 0.6515 - val_loss: 6.8752 - val_acc: 0.5114
Epoch 24/50
6512/6680 [============================>.] - ETA: 0s - loss: 5.5862 - acc: 0.6528Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6040 - acc: 0.6516 - val_loss: 6.8665 - val_acc: 0.5114
Epoch 25/50
6327/6680 [===========================>..] - ETA: 0s - loss: 5.6180 - acc: 0.6510Epoch 00025: val_loss improved from 6.85111 to 6.84701, saving model to saved_models1/weights.best.vgg16_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 166us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8470 - val_acc: 0.5102
Epoch 26/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6026 - acc: 0.6516Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6050 - acc: 0.6515 - val_loss: 6.8515 - val_acc: 0.5090
Epoch 27/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.6025 - acc: 0.6520Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6033 - acc: 0.6519 - val_loss: 6.8857 - val_acc: 0.5054
Epoch 28/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.5879 - acc: 0.6528Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6038 - acc: 0.6518 - val_loss: 6.8648 - val_acc: 0.5078
Epoch 29/50
6623/6680 [============================>.] - ETA: 0s - loss: 5.6017 - acc: 0.6521Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6045 - acc: 0.6519 - val_loss: 6.8795 - val_acc: 0.5126
Epoch 30/50
6549/6680 [============================>.] - ETA: 0s - loss: 5.5873 - acc: 0.6529Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6032 - acc: 0.6519 - val_loss: 6.8599 - val_acc: 0.5126
Epoch 31/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.5879 - acc: 0.6529Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6057 - acc: 0.6518 - val_loss: 6.8663 - val_acc: 0.5102
Epoch 32/50
6623/6680 [============================>.] - ETA: 0s - loss: 5.6117 - acc: 0.6514Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8608 - val_acc: 0.5114
Epoch 33/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6278 - acc: 0.6505Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6051 - acc: 0.6519 - val_loss: 6.8632 - val_acc: 0.5078
Epoch 34/50
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5994 - acc: 0.6521Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8730 - val_acc: 0.5090
Epoch 35/50
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5908 - acc: 0.6524Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8830 - val_acc: 0.5078
Epoch 36/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6273 - acc: 0.6504Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8658 - val_acc: 0.5078
Epoch 37/50
6438/6680 [===========================>..] - ETA: 0s - loss: 5.5717 - acc: 0.6538Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8692 - val_acc: 0.5090
Epoch 38/50
6660/6680 [============================>.] - ETA: 0s - loss: 5.5996 - acc: 0.6521Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8767 - val_acc: 0.5042
Epoch 39/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.5892 - acc: 0.6526Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8628 - val_acc: 0.5066
Epoch 40/50
6475/6680 [============================>.] - ETA: 0s - loss: 5.6199 - acc: 0.6510Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6519 - val_loss: 6.8755 - val_acc: 0.5042
Epoch 41/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.5999 - acc: 0.6521Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6056 - acc: 0.6518 - val_loss: 6.8799 - val_acc: 0.5018
Epoch 42/50
6623/6680 [============================>.] - ETA: 0s - loss: 5.6048 - acc: 0.6521Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6052 - acc: 0.6521 - val_loss: 6.8781 - val_acc: 0.5006
Epoch 43/50
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6117 - acc: 0.6514Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 163us/step - loss: 5.6039 - acc: 0.6519 - val_loss: 6.8826 - val_acc: 0.5006
Epoch 44/50
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6244 - acc: 0.6504Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6040 - acc: 0.6516 - val_loss: 6.8885 - val_acc: 0.5054
Epoch 45/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.6183 - acc: 0.6510Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8818 - val_acc: 0.5066
Epoch 46/50
6438/6680 [===========================>..] - ETA: 0s - loss: 5.5737 - acc: 0.6535Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8721 - val_acc: 0.5078
Epoch 47/50
6401/6680 [===========================>..] - ETA: 0s - loss: 5.5876 - acc: 0.6529Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8823 - val_acc: 0.5078
Epoch 48/50
6586/6680 [============================>.] - ETA: 0s - loss: 5.5992 - acc: 0.6523Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 166us/step - loss: 5.6048 - acc: 0.6519 - val_loss: 6.8934 - val_acc: 0.5054
Epoch 49/50
6438/6680 [===========================>..] - ETA: 0s - loss: 5.6154 - acc: 0.6513Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6026 - acc: 0.6521 - val_loss: 6.8890 - val_acc: 0.5066
Epoch 50/50
6364/6680 [===========================>..] - ETA: 0s - loss: 5.5937 - acc: 0.6526Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 165us/step - loss: 5.6042 - acc: 0.6519 - val_loss: 6.8951 - val_acc: 0.5066

Batch size=40 Epoch=20
Train on 6680 samples, validate on 835 samples
Epoch 1/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6009 - acc: 0.6520Epoch 00001: val_loss improved from inf to 6.87440, saving model to saved_models1/weights.best.vgg16_bs40_ep20.hdf5
6680/6680 [==============================] - 1s 159us/step - loss: 5.6019 - acc: 0.6519 - val_loss: 6.8744 - val_acc: 0.5054
Epoch 2/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6258 - acc: 0.6508Epoch 00002: val_loss improved from 6.87440 to 6.86759, saving model to saved_models1/weights.best.vgg16_bs40_ep20.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8676 - val_acc: 0.5090
Epoch 3/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6279 - acc: 0.6505Epoch 00003: val_loss improved from 6.86759 to 6.84342, saving model to saved_models1/weights.best.vgg16_bs40_ep20.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8434 - val_acc: 0.5102
Epoch 4/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6166 - acc: 0.6511Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8579 - val_acc: 0.5078
Epoch 5/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5921 - acc: 0.6525Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6054 - acc: 0.6516 - val_loss: 6.8680 - val_acc: 0.5018
Epoch 6/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6334 - acc: 0.6498Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8579 - val_acc: 0.5042
Epoch 7/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6121 - acc: 0.6515Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6031 - acc: 0.6521 - val_loss: 6.8837 - val_acc: 0.5078
Epoch 8/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5934 - acc: 0.6526Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6042 - acc: 0.6519 - val_loss: 6.8533 - val_acc: 0.5126
Epoch 9/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6134 - acc: 0.6512Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6044 - acc: 0.6518 - val_loss: 6.8688 - val_acc: 0.5090
Epoch 10/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6048 - acc: 0.6520Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6033 - acc: 0.6521 - val_loss: 6.8796 - val_acc: 0.5054
Epoch 11/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6072 - acc: 0.6517Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6032 - acc: 0.6519 - val_loss: 6.8863 - val_acc: 0.5114
Epoch 12/20
6640/6680 [============================>.] - ETA: 0s - loss: 5.5968 - acc: 0.6523Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 164us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8661 - val_acc: 0.5102
Epoch 13/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6111 - acc: 0.6515Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6045 - acc: 0.6519 - val_loss: 6.8827 - val_acc: 0.5114
Epoch 14/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.6076 - acc: 0.6515Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6036 - acc: 0.6518 - val_loss: 6.8951 - val_acc: 0.5078
Epoch 15/20
6480/6680 [============================>.] - ETA: 0s - loss: 5.5797 - acc: 0.6532Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6057 - acc: 0.6516 - val_loss: 6.8663 - val_acc: 0.5138
Epoch 16/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5924 - acc: 0.6526Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6037 - acc: 0.6518 - val_loss: 6.8629 - val_acc: 0.5150
Epoch 17/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5979 - acc: 0.6523Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8597 - val_acc: 0.5126
Epoch 18/20
6560/6680 [============================>.] - ETA: 0s - loss: 5.6093 - acc: 0.6515Epoch 00018: val_loss improved from 6.84342 to 6.84174, saving model to saved_models1/weights.best.vgg16_bs40_ep20.hdf5
6680/6680 [==============================] - 1s 157us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8417 - val_acc: 0.5138
Epoch 19/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5705 - acc: 0.6538Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8682 - val_acc: 0.5150
Epoch 20/20
6520/6680 [============================>.] - ETA: 0s - loss: 5.5919 - acc: 0.6523Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6051 - acc: 0.6515 - val_loss: 6.8459 - val_acc: 0.5138

Batch size=40 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6213 - acc: 0.6509Epoch 00001: val_loss improved from inf to 6.85722, saving model to saved_models1/weights.best.vgg16_bs40_ep35.hdf5
6680/6680 [==============================] - 1s 159us/step - loss: 5.6049 - acc: 0.6519 - val_loss: 6.8572 - val_acc: 0.5138
Epoch 2/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5778 - acc: 0.6537Epoch 00002: val_loss improved from 6.85722 to 6.85657, saving model to saved_models1/weights.best.vgg16_bs40_ep35.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8566 - val_acc: 0.5138
Epoch 3/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6149 - acc: 0.6514Epoch 00003: val_loss improved from 6.85657 to 6.84041, saving model to saved_models1/weights.best.vgg16_bs40_ep35.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6059 - acc: 0.6519 - val_loss: 6.8404 - val_acc: 0.5114
Epoch 4/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6286 - acc: 0.6503Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8492 - val_acc: 0.5126
Epoch 5/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.6016 - acc: 0.6521Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8738 - val_acc: 0.5126
Epoch 6/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6074 - acc: 0.6515Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6034 - acc: 0.6518 - val_loss: 6.8721 - val_acc: 0.5138
Epoch 7/35
6480/6680 [============================>.] - ETA: 0s - loss: 5.5914 - acc: 0.6523Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6049 - acc: 0.6515 - val_loss: 6.8715 - val_acc: 0.5114
Epoch 8/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.5812 - acc: 0.6535Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6040 - acc: 0.6521 - val_loss: 6.8734 - val_acc: 0.5126
Epoch 9/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5799 - acc: 0.6532Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8857 - val_acc: 0.5126
Epoch 10/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5946 - acc: 0.6523Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6054 - acc: 0.6516 - val_loss: 6.8780 - val_acc: 0.5138
Epoch 11/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5995 - acc: 0.6520Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8733 - val_acc: 0.5126
Epoch 12/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6058 - acc: 0.6517Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8719 - val_acc: 0.5186
Epoch 13/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.6221 - acc: 0.6508Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6055 - acc: 0.6518 - val_loss: 6.8712 - val_acc: 0.5102
Epoch 14/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6164 - acc: 0.6509Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8817 - val_acc: 0.5126
Epoch 15/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5801 - acc: 0.6531Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8812 - val_acc: 0.5126
Epoch 16/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5993 - acc: 0.6520Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6051 - acc: 0.6516 - val_loss: 6.8837 - val_acc: 0.5102
Epoch 17/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6175 - acc: 0.6514Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6036 - acc: 0.6522 - val_loss: 6.8612 - val_acc: 0.5126
Epoch 18/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5607 - acc: 0.6548Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6058 - acc: 0.6519 - val_loss: 6.8649 - val_acc: 0.5126
Epoch 19/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6298 - acc: 0.6505Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6060 - acc: 0.6519 - val_loss: 6.8638 - val_acc: 0.5126
Epoch 20/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6041 - acc: 0.6518Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6050 - acc: 0.6518 - val_loss: 6.8502 - val_acc: 0.5162
Epoch 21/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6005 - acc: 0.6523Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6042 - acc: 0.6519 - val_loss: 6.8828 - val_acc: 0.5090
Epoch 22/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5861 - acc: 0.6532Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6043 - acc: 0.6521 - val_loss: 6.8599 - val_acc: 0.5126
Epoch 23/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6053 - acc: 0.6515Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6037 - acc: 0.6516 - val_loss: 6.8728 - val_acc: 0.5102
Epoch 24/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6063 - acc: 0.6518Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6023 - acc: 0.6521 - val_loss: 6.8734 - val_acc: 0.5162
Epoch 25/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6032 - acc: 0.6517Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6042 - acc: 0.6516 - val_loss: 6.8669 - val_acc: 0.5102
Epoch 26/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6088 - acc: 0.6517Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8625 - val_acc: 0.5138
Epoch 27/35
6480/6680 [============================>.] - ETA: 0s - loss: 5.5729 - acc: 0.6537Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 160us/step - loss: 5.6039 - acc: 0.6518 - val_loss: 6.8727 - val_acc: 0.5114
Epoch 28/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.6095 - acc: 0.6515Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6518 - val_loss: 6.8748 - val_acc: 0.5126
Epoch 29/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.5968 - acc: 0.6526Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6052 - acc: 0.6521 - val_loss: 6.8568 - val_acc: 0.5126
Epoch 30/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6517Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8715 - val_acc: 0.5102
Epoch 31/35
6560/6680 [============================>.] - ETA: 0s - loss: 5.5791 - acc: 0.6532Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6043 - acc: 0.6516 - val_loss: 6.8915 - val_acc: 0.5090
Epoch 32/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6161 - acc: 0.6512Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8810 - val_acc: 0.5114
Epoch 33/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6109 - acc: 0.6515Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6030 - acc: 0.6519 - val_loss: 6.8774 - val_acc: 0.5138
Epoch 34/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6057 - acc: 0.6518Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8897 - val_acc: 0.5138
Epoch 35/35
6520/6680 [============================>.] - ETA: 0s - loss: 5.6175 - acc: 0.6511Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6053 - acc: 0.6518 - val_loss: 6.8729 - val_acc: 0.5138

Batch size=40 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5855 - acc: 0.6529Epoch 00001: val_loss improved from inf to 6.87384, saving model to saved_models1/weights.best.vgg16_bs40_ep40.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6038 - acc: 0.6518 - val_loss: 6.8738 - val_acc: 0.5114
Epoch 2/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6225 - acc: 0.6508Epoch 00002: val_loss improved from 6.87384 to 6.83667, saving model to saved_models1/weights.best.vgg16_bs40_ep40.hdf5
6680/6680 [==============================] - 1s 159us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8367 - val_acc: 0.5150
Epoch 3/40
6480/6680 [============================>.] - ETA: 0s - loss: 5.6034 - acc: 0.6519Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 160us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8666 - val_acc: 0.5102
Epoch 4/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6105 - acc: 0.6515Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6040 - acc: 0.6519 - val_loss: 6.8713 - val_acc: 0.5114
Epoch 5/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5983 - acc: 0.6523Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8623 - val_acc: 0.5126
Epoch 6/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5807 - acc: 0.6534Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6039 - acc: 0.6519 - val_loss: 6.8483 - val_acc: 0.5114
Epoch 7/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6105 - acc: 0.6514Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6040 - acc: 0.6518 - val_loss: 6.8488 - val_acc: 0.5090
Epoch 8/40
6560/6680 [============================>.] - ETA: 0s - loss: 5.5965 - acc: 0.6523Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8663 - val_acc: 0.5078
Epoch 9/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6160 - acc: 0.6511Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8530 - val_acc: 0.5066
Epoch 10/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5888 - acc: 0.6526Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8681 - val_acc: 0.5102
Epoch 11/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6258 - acc: 0.6503Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6045 - acc: 0.6516 - val_loss: 6.8781 - val_acc: 0.5078
Epoch 12/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6061 - acc: 0.6518Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8908 - val_acc: 0.5066
Epoch 13/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6043 - acc: 0.6518Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8522 - val_acc: 0.5126
Epoch 14/40
6560/6680 [============================>.] - ETA: 0s - loss: 5.6048 - acc: 0.6518Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 155us/step - loss: 5.6055 - acc: 0.6518 - val_loss: 6.8582 - val_acc: 0.5102
Epoch 15/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6143 - acc: 0.6511Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8598 - val_acc: 0.5102
Epoch 16/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6515Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8732 - val_acc: 0.5114
Epoch 17/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5731 - acc: 0.6537Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6037 - acc: 0.6518 - val_loss: 6.9067 - val_acc: 0.5090
Epoch 18/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6002 - acc: 0.6523Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6036 - acc: 0.6521 - val_loss: 6.8628 - val_acc: 0.5102
Epoch 19/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5948 - acc: 0.6525Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8764 - val_acc: 0.5078
Epoch 20/40
6560/6680 [============================>.] - ETA: 0s - loss: 5.5847 - acc: 0.6529Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6050 - acc: 0.6516 - val_loss: 6.8660 - val_acc: 0.5090
Epoch 21/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6307 - acc: 0.6502Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8850 - val_acc: 0.5030
Epoch 22/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6135 - acc: 0.6512Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8731 - val_acc: 0.5102
Epoch 23/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6097 - acc: 0.6518Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6048 - acc: 0.6521 - val_loss: 6.8673 - val_acc: 0.5102
Epoch 24/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6076 - acc: 0.6515Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6043 - acc: 0.6516 - val_loss: 6.8731 - val_acc: 0.5126
Epoch 25/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.5988 - acc: 0.6523Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6047 - acc: 0.6519 - val_loss: 6.8453 - val_acc: 0.5138
Epoch 26/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6100 - acc: 0.6515Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6035 - acc: 0.6519 - val_loss: 6.8610 - val_acc: 0.5126
Epoch 27/40
6520/6680 [============================>.] - ETA: 0s - loss: 5.6255 - acc: 0.6505Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8644 - val_acc: 0.5090
Epoch 28/40
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6194 - acc: 0.6508Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 168us/step - loss: 5.6033 - acc: 0.6518 - val_loss: 6.8612 - val_acc: 0.5114
Epoch 29/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6515Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8646 - val_acc: 0.5126
Epoch 30/40
6360/6680 [===========================>..] - ETA: 0s - loss: 5.5935 - acc: 0.6525Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6055 - acc: 0.6518 - val_loss: 6.8641 - val_acc: 0.5102
Epoch 31/40
6360/6680 [===========================>..] - ETA: 0s - loss: 5.6196 - acc: 0.6509Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.9054 - val_acc: 0.5066
Epoch 32/40
6360/6680 [===========================>..] - ETA: 0s - loss: 5.6364 - acc: 0.6497Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 173us/step - loss: 5.6052 - acc: 0.6516 - val_loss: 6.8873 - val_acc: 0.5066
Epoch 33/40
6400/6680 [===========================>..] - ETA: 0s - loss: 5.6109 - acc: 0.6516Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 171us/step - loss: 5.6040 - acc: 0.6519 - val_loss: 6.8749 - val_acc: 0.5090
Epoch 34/40
6400/6680 [===========================>..] - ETA: 0s - loss: 5.5707 - acc: 0.6539Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6026 - acc: 0.6519 - val_loss: 6.9069 - val_acc: 0.5066
Epoch 35/40
6600/6680 [============================>.] - ETA: 0s - loss: 5.5870 - acc: 0.6529Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6034 - acc: 0.6518 - val_loss: 6.8660 - val_acc: 0.5114
Epoch 36/40
6640/6680 [============================>.] - ETA: 0s - loss: 5.6016 - acc: 0.6521Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 169us/step - loss: 5.6043 - acc: 0.6519 - val_loss: 6.8671 - val_acc: 0.5102
Epoch 37/40
6360/6680 [===========================>..] - ETA: 0s - loss: 5.5865 - acc: 0.6530Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6036 - acc: 0.6519 - val_loss: 6.8622 - val_acc: 0.5078
Epoch 38/40
6640/6680 [============================>.] - ETA: 0s - loss: 5.5979 - acc: 0.6523Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 168us/step - loss: 5.6054 - acc: 0.6518 - val_loss: 6.8664 - val_acc: 0.5138
Epoch 39/40
6400/6680 [===========================>..] - ETA: 0s - loss: 5.6100 - acc: 0.6516Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 170us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8497 - val_acc: 0.5114
Epoch 40/40
6440/6680 [===========================>..] - ETA: 0s - loss: 5.6080 - acc: 0.6514Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 167us/step - loss: 5.6044 - acc: 0.6516 - val_loss: 6.8734 - val_acc: 0.5126

Batch size=40 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6360/6680 [===========================>..] - ETA: 0s - loss: 5.6242 - acc: 0.6508Epoch 00001: val_loss improved from inf to 6.87814, saving model to saved_models1/weights.best.vgg16_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 169us/step - loss: 5.6045 - acc: 0.6519 - val_loss: 6.8781 - val_acc: 0.5114
Epoch 2/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5702 - acc: 0.6538Epoch 00002: val_loss improved from 6.87814 to 6.85458, saving model to saved_models1/weights.best.vgg16_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 159us/step - loss: 5.6033 - acc: 0.6518 - val_loss: 6.8546 - val_acc: 0.5150
Epoch 3/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6078 - acc: 0.6517Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6037 - acc: 0.6519 - val_loss: 6.8650 - val_acc: 0.5138
Epoch 4/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6209 - acc: 0.6506Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6045 - acc: 0.6516 - val_loss: 6.8767 - val_acc: 0.5162
Epoch 5/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6264 - acc: 0.6508Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6050 - acc: 0.6521 - val_loss: 6.8581 - val_acc: 0.5114
Epoch 6/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6172 - acc: 0.6509Epoch 00006: val_loss improved from 6.85458 to 6.83943, saving model to saved_models1/weights.best.vgg16_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 160us/step - loss: 5.6034 - acc: 0.6518 - val_loss: 6.8394 - val_acc: 0.5126
Epoch 7/50
6560/6680 [============================>.] - ETA: 0s - loss: 5.5844 - acc: 0.6529Epoch 00007: val_loss improved from 6.83943 to 6.82535, saving model to saved_models1/weights.best.vgg16_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 158us/step - loss: 5.6048 - acc: 0.6516 - val_loss: 6.8254 - val_acc: 0.5126
Epoch 8/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6092 - acc: 0.6512Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6052 - acc: 0.6515 - val_loss: 6.8258 - val_acc: 0.5126
Epoch 9/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6379 - acc: 0.6497Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6042 - acc: 0.6518 - val_loss: 6.8590 - val_acc: 0.5126
Epoch 10/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6187 - acc: 0.6509Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8386 - val_acc: 0.5126
Epoch 11/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5939 - acc: 0.6526Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6046 - acc: 0.6519 - val_loss: 6.8385 - val_acc: 0.5126
Epoch 12/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6061 - acc: 0.6515Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6046 - acc: 0.6516 - val_loss: 6.8433 - val_acc: 0.5114
Epoch 13/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6045 - acc: 0.6518Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6054 - acc: 0.6518 - val_loss: 6.8543 - val_acc: 0.5090
Epoch 14/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6232 - acc: 0.6505Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6044 - acc: 0.6516 - val_loss: 6.8586 - val_acc: 0.5090
Epoch 15/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6104 - acc: 0.6512Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6039 - acc: 0.6516 - val_loss: 6.8651 - val_acc: 0.5054
Epoch 16/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6078 - acc: 0.6517Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6038 - acc: 0.6519 - val_loss: 6.8593 - val_acc: 0.5102
Epoch 17/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5871 - acc: 0.6526Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8562 - val_acc: 0.5102
Epoch 18/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6005 - acc: 0.6518Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6039 - acc: 0.6516 - val_loss: 6.8449 - val_acc: 0.5102
Epoch 19/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6316 - acc: 0.6502Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6053 - acc: 0.6518 - val_loss: 6.8905 - val_acc: 0.5054
Epoch 20/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6235 - acc: 0.6506Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6046 - acc: 0.6518 - val_loss: 6.8910 - val_acc: 0.5090
Epoch 21/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6044 - acc: 0.6515Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 159us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8793 - val_acc: 0.5114
Epoch 22/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6020 - acc: 0.6517Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6515 - val_loss: 6.8816 - val_acc: 0.5090
Epoch 23/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6137 - acc: 0.6512Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8727 - val_acc: 0.5102
Epoch 24/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6258 - acc: 0.6505Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6044 - acc: 0.6518 - val_loss: 6.8731 - val_acc: 0.5078
Epoch 25/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5962 - acc: 0.6523Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8697 - val_acc: 0.5114
Epoch 26/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5995 - acc: 0.6520Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8673 - val_acc: 0.5114
Epoch 27/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6119 - acc: 0.6512Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8905 - val_acc: 0.5090
Epoch 28/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6177 - acc: 0.6512Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6062 - acc: 0.6519 - val_loss: 6.8900 - val_acc: 0.5090
Epoch 29/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6087 - acc: 0.6515Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8958 - val_acc: 0.5138
Epoch 30/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6330 - acc: 0.6500Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6043 - acc: 0.6518 - val_loss: 6.8818 - val_acc: 0.5162
Epoch 31/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6088 - acc: 0.6515Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6048 - acc: 0.6518 - val_loss: 6.8841 - val_acc: 0.5126
Epoch 32/50
6480/6680 [============================>.] - ETA: 0s - loss: 5.6224 - acc: 0.6509Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 159us/step - loss: 5.6037 - acc: 0.6521 - val_loss: 6.8863 - val_acc: 0.5078
Epoch 33/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5968 - acc: 0.6523Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6051 - acc: 0.6518 - val_loss: 6.8655 - val_acc: 0.5078
Epoch 34/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6100 - acc: 0.6514Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6035 - acc: 0.6518 - val_loss: 6.8696 - val_acc: 0.5066
Epoch 35/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6053 - acc: 0.6515Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6038 - acc: 0.6516 - val_loss: 6.8501 - val_acc: 0.5090
Epoch 36/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5902 - acc: 0.6529Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6059 - acc: 0.6519 - val_loss: 6.8472 - val_acc: 0.5138
Epoch 37/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5881 - acc: 0.6531Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 159us/step - loss: 5.6039 - acc: 0.6521 - val_loss: 6.8530 - val_acc: 0.5138
Epoch 38/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6080 - acc: 0.6517Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6039 - acc: 0.6519 - val_loss: 6.8452 - val_acc: 0.5102
Epoch 39/50
6560/6680 [============================>.] - ETA: 0s - loss: 5.5853 - acc: 0.6532Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6056 - acc: 0.6519 - val_loss: 6.8565 - val_acc: 0.5090
Epoch 40/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6272 - acc: 0.6505Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6052 - acc: 0.6518 - val_loss: 6.8572 - val_acc: 0.5114
Epoch 41/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5898 - acc: 0.6528Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6031 - acc: 0.6519 - val_loss: 6.8719 - val_acc: 0.5114
Epoch 42/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6176 - acc: 0.6509Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6047 - acc: 0.6516 - val_loss: 6.8774 - val_acc: 0.5114
Epoch 43/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6000 - acc: 0.6521Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8696 - val_acc: 0.5102
Epoch 44/50
6560/6680 [============================>.] - ETA: 0s - loss: 5.6065 - acc: 0.6517Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 156us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8733 - val_acc: 0.5090
Epoch 45/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6036 - acc: 0.6518Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8639 - val_acc: 0.5150
Epoch 46/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5922 - acc: 0.6525Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6055 - acc: 0.6516 - val_loss: 6.8612 - val_acc: 0.5102
Epoch 47/50
6560/6680 [============================>.] - ETA: 0s - loss: 5.6219 - acc: 0.6506Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6053 - acc: 0.6516 - val_loss: 6.8629 - val_acc: 0.5102
Epoch 48/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6229 - acc: 0.6508Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 158us/step - loss: 5.6041 - acc: 0.6519 - val_loss: 6.8646 - val_acc: 0.5090
Epoch 49/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.5914 - acc: 0.6526Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6047 - acc: 0.6518 - val_loss: 6.8507 - val_acc: 0.5162
Epoch 50/50
6520/6680 [============================>.] - ETA: 0s - loss: 5.6135 - acc: 0.6512Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 157us/step - loss: 5.6045 - acc: 0.6518 - val_loss: 6.8720 - val_acc: 0.5138
In [26]:
import pandas as pd
pd.DataFrame(fitingdict_vgg16)
Out[26]:
Batch_Size Epochs Test_Accuracy
0 20 20 45.813397
1 20 35 51.196172
2 20 40 52.033493
3 20 50 52.870813
4 35 20 52.631579
5 35 35 52.870813
6 35 40 53.110048
7 35 50 52.990431
8 37 20 52.990431
9 37 35 52.751196
10 37 40 52.631579
11 37 50 52.990431
12 40 20 52.511962
13 40 35 52.751196
14 40 40 52.272727
15 40 50 52.751196

Load the Model with the Best Validation Loss

In [21]:
#take largest testaccuracy's batch size and epochs
ind=fitingdict_vgg16['Test_Accuracy'].index(max(fitingdict_vgg16['Test_Accuracy']))
bs=fitingdict_vgg16['Batch_Size'][ind]
ep=fitingdict_vgg16['Epochs'][ind]

#LOAD the model with Best validation loss 
VGG16_model.load_weights('saved_models1/weights.best.vgg16_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')

Test the Model

Now, we can use the CNN to test how well it identifies breed within our test dataset of dog images. We print the test accuracy below.

In [20]:
# get index of predicted dog breed for each image in test set
VGG16_predictions = [np.argmax(VGG16_model.predict(np.expand_dims(feature, axis=0))) for feature in test_VGG16]

# report test accuracy
test_accuracy = 100*np.sum(np.array(VGG16_predictions)==np.argmax(test_targets, axis=1))/len(VGG16_predictions)
print('Test accuracy: %.4f%%' % test_accuracy)
Test accuracy: 53.1100%

Predict Dog Breed with the Model

In [23]:
from extract_bottleneck_features import *

def VGG16_predict_breed(img_path):
    # extract bottleneck features
    bottleneck_feature = extract_VGG16(path_to_tensor(img_path))
    # obtain predicted vector
    predicted_vector = VGG16_model.predict(bottleneck_feature)
    # return dog breed that is predicted by the model
    return dog_names[np.argmax(predicted_vector)]
In [24]:
### TODO: Write your algorithm.
### Feel free to use as many code cells as needed.
from keras.preprocessing import image                  
from os import walk
from os import listdir
from os.path import isfile, join
import random
import numpy as np
import cv2


def show_image(path):
    img = image.load_img(path, target_size=(224, 224))
    img = image.img_to_array(img)
    plt.imshow(img/255)
    plt.show()
    

def whos_face_is_this_VGG16(img_path):
    if(dog_detector(img_path)):
        print("\n**************************************")
        show_image(img_path)
        print("hello, Doggy!")
        print("Your predicted breed is....")
        print(VGG16_predict_breed(img_path))
        
    elif(humanface_detector(img_path)):
        print("\n**************************************")
        show_image(img_path)
        print("Hello, Human!")
        print("You look like a.... ")
        print(VGG16_predict_breed(img_path))
        
    else:
        print("\n**************************************")
        show_image(img_path)
        print("**No face detected..ERROR..**")
In [37]:
#Load the img files
imgs=["dog_images/doggy (1).jpg","dog_images/doggy (1a).jpg","Hooman_images/hooman (4).jpg","Hooman_images/hooman (10).jpg"]
for img in imgs:
    whos_face_is_this_VGG16(img)
**************************************
hello, Doggy!
Your predicted breed is....
Boykin_spaniel

**************************************
hello, Doggy!
Your predicted breed is....
Irish_water_spaniel

**************************************
**No face detected..ERROR..**

**************************************
Hello, Human!
You look like a.... 
Dachshund

Above model VGG16 correctly differentiate 2 similar looking dogs into _Boykin_spaniel and Irish_waterspaniel . But, dog predicted _Boykinspaniel was actually _American_waterspaniel the wrong prediction here due to Test accuracy of the model is 53.1100% .

This was letter corrected by Xception model giving test acccuracy of 86.8421% .


Step 5: Create a CNN to Classify Dog Breeds (using Transfer Learning)

You will now use transfer learning to create a CNN that can identify dog breed from images. Your CNN must attain at least 60% accuracy on the test set.

In Step 4, we used transfer learning to create a CNN using VGG-16 bottleneck features. In this section, you must use the bottleneck features from a different pre-trained model. To make things easier for you, we have pre-computed the features for all of the networks that are currently available in Keras. These are already in the workspace, at /data/bottleneck_features. If you wish to download them on a different machine, they can be found at:

The files are encoded as such:

Dog{network}Data.npz

where {network}, in the above filename, can be one of VGG19, Resnet50, InceptionV3, or Xception.

The above architectures are downloaded and stored for you in the /data/bottleneck_features/ folder.

This means the following will be in the /data/bottleneck_features/ folder:

DogVGG19Data.npz DogResnet50Data.npz DogInceptionV3Data.npz DogXceptionData.npz

(IMPLEMENTATION) Obtain Bottleneck Features

In the code block below, extract the bottleneck features corresponding to the train, test, and validation sets by running the following:

bottleneck_features = np.load('/data/bottleneck_features/Dog{network}Data.npz')
train_{network} = bottleneck_features['train']
valid_{network} = bottleneck_features['valid']
test_{network} = bottleneck_features['test']

Lests do with ResNet-50

In [32]:
### TODO: Obtain bottleneck features from another pre-trained CNN.
bottleneck_features = np.load('/data/bottleneck_features/DogResnet50Data.npz')
train_Resnet50 = bottleneck_features['train']
valid_Resnet50 = bottleneck_features['valid']
test_Resnet50 = bottleneck_features['test']


### TODO: Define your architecture.
from keras.layers import Conv2D, MaxPooling2D, GlobalAveragePooling2D
from keras.layers import Dropout, Flatten, Dense, Activation
from keras.models import Sequential

ResNet_model = Sequential()
ResNet_model.add(GlobalAveragePooling2D(input_shape=train_Resnet50.shape[1:]))
ResNet_model.add(Dense(133, activation='softmax'))

ResNet_model.summary()
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
global_average_pooling2d_4 ( (None, 2048)              0         
_________________________________________________________________
dense_4 (Dense)              (None, 133)               272517    
=================================================================
Total params: 272,517
Trainable params: 272,517
Non-trainable params: 0
_________________________________________________________________
In [33]:
### TODO: Compile the model
ResNet_model.compile(loss="categorical_crossentropy",optimizer="rmsprop",metrics=["accuracy"])

### TODO: Train the model.

batch_size = [35,37,40,64]
epochs = [25,35,50]

fitingdict_ResNet={'Batch_Size':[], 
            'Epochs':[],
            'Test_Accuracy':[]}

for bs in batch_size:
    for ep in epochs:
        checkpointer = ModelCheckpoint(filepath='saved_models3/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5', 
                               verbose=1, save_best_only=True)
        print("\nBatch size={0} Epoch={1}".format(bs,ep))
        ResNet_model.fit(train_Resnet50, train_targets,validation_data=(valid_Resnet50, valid_targets),
                          epochs=ep , batch_size=bs,
                          callbacks=[checkpointer],verbose=1)

        #LOAD the model with Best validation loss
        ResNet_model.load_weights('saved_models3/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')

        
        ResNet_predictions = [np.argmax(ResNet_model.predict(np.expand_dims(feature, axis=0))) for feature in test_Resnet50]
        test_accuracy = 100*np.sum(np.array(ResNet_predictions)==np.argmax(test_targets, axis=1))/len(ResNet_predictions)
        fitingdict_ResNet['Batch_Size'].append(bs)
        fitingdict_ResNet['Epochs'].append(ep)
        fitingdict_ResNet['Test_Accuracy'].append(test_accuracy)
Batch size=35 Epoch=25
Train on 6680 samples, validate on 835 samples
Epoch 1/25
6545/6680 [============================>.] - ETA: 0s - loss: 1.8384 - acc: 0.5630Epoch 00001: val_loss improved from inf to 0.89360, saving model to saved_models3/weights.best.ResNet_bs35_ep25.hdf5
6680/6680 [==============================] - 1s 204us/step - loss: 1.8207 - acc: 0.5659 - val_loss: 0.8936 - val_acc: 0.7246
Epoch 2/25
6475/6680 [============================>.] - ETA: 0s - loss: 0.4679 - acc: 0.8593Epoch 00002: val_loss improved from 0.89360 to 0.72643, saving model to saved_models3/weights.best.ResNet_bs35_ep25.hdf5
6680/6680 [==============================] - 1s 152us/step - loss: 0.4684 - acc: 0.8594 - val_loss: 0.7264 - val_acc: 0.7808
Epoch 3/25
6370/6680 [===========================>..] - ETA: 0s - loss: 0.2605 - acc: 0.9226Epoch 00003: val_loss improved from 0.72643 to 0.64135, saving model to saved_models3/weights.best.ResNet_bs35_ep25.hdf5
6680/6680 [==============================] - 1s 145us/step - loss: 0.2609 - acc: 0.9213 - val_loss: 0.6414 - val_acc: 0.7988
Epoch 4/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.1601 - acc: 0.9541Epoch 00004: val_loss improved from 0.64135 to 0.62651, saving model to saved_models3/weights.best.ResNet_bs35_ep25.hdf5
6680/6680 [==============================] - 1s 140us/step - loss: 0.1594 - acc: 0.9543 - val_loss: 0.6265 - val_acc: 0.8144
Epoch 5/25
6475/6680 [============================>.] - ETA: 0s - loss: 0.1107 - acc: 0.9705Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.1129 - acc: 0.9696 - val_loss: 0.6381 - val_acc: 0.8096
Epoch 6/25
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0738 - acc: 0.9825Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0743 - acc: 0.9823 - val_loss: 0.6644 - val_acc: 0.8144
Epoch 7/25
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0509 - acc: 0.9880Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0516 - acc: 0.9879 - val_loss: 0.6700 - val_acc: 0.8084
Epoch 8/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0367 - acc: 0.9910Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0367 - acc: 0.9910 - val_loss: 0.6378 - val_acc: 0.8192
Epoch 9/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0266 - acc: 0.9935Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0266 - acc: 0.9936 - val_loss: 0.6611 - val_acc: 0.8120
Epoch 10/25
6545/6680 [============================>.] - ETA: 0s - loss: 0.0197 - acc: 0.9960Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0197 - acc: 0.9961 - val_loss: 0.6787 - val_acc: 0.8275
Epoch 11/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0161 - acc: 0.9970Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0159 - acc: 0.9970 - val_loss: 0.6935 - val_acc: 0.8275
Epoch 12/25
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0118 - acc: 0.9974Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0120 - acc: 0.9973 - val_loss: 0.6982 - val_acc: 0.8371
Epoch 13/25
6475/6680 [============================>.] - ETA: 0s - loss: 0.0118 - acc: 0.9981Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0117 - acc: 0.9981 - val_loss: 0.7255 - val_acc: 0.8275
Epoch 14/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0085 - acc: 0.9980Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0084 - acc: 0.9981 - val_loss: 0.7602 - val_acc: 0.8371
Epoch 15/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0074 - acc: 0.9982Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0073 - acc: 0.9982 - val_loss: 0.8233 - val_acc: 0.8132
Epoch 16/25
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0066 - acc: 0.9986Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0067 - acc: 0.9985 - val_loss: 0.8173 - val_acc: 0.8263
Epoch 17/25
6580/6680 [============================>.] - ETA: 0s - loss: 0.0060 - acc: 0.9982Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0060 - acc: 0.9982 - val_loss: 0.8164 - val_acc: 0.8299
Epoch 18/25
6475/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9985Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 0.7978 - val_acc: 0.8347
Epoch 19/25
6510/6680 [============================>.] - ETA: 0s - loss: 0.0060 - acc: 0.9986Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0058 - acc: 0.9987 - val_loss: 0.8421 - val_acc: 0.8407
Epoch 20/25
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0051 - acc: 0.9986Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 0.8878 - val_acc: 0.8323
Epoch 21/25
6335/6680 [===========================>..] - ETA: 0s - loss: 0.0032 - acc: 0.9984Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0031 - acc: 0.9985 - val_loss: 0.9068 - val_acc: 0.8299
Epoch 22/25
6545/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0048 - acc: 0.9987 - val_loss: 0.8950 - val_acc: 0.8383
Epoch 23/25
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0032 - acc: 0.9988Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 0.9336 - val_acc: 0.8407
Epoch 24/25
6475/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9991Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0042 - acc: 0.9991 - val_loss: 0.9333 - val_acc: 0.8263
Epoch 25/25
6265/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 0.9509 - val_acc: 0.8371

Batch size=35 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.1190 - acc: 0.9664Epoch 00001: val_loss improved from inf to 0.64755, saving model to saved_models3/weights.best.ResNet_bs35_ep35.hdf5
6680/6680 [==============================] - 1s 140us/step - loss: 0.1187 - acc: 0.9666 - val_loss: 0.6475 - val_acc: 0.7976
Epoch 2/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0740 - acc: 0.9796Epoch 00002: val_loss improved from 0.64755 to 0.61231, saving model to saved_models3/weights.best.ResNet_bs35_ep35.hdf5
6680/6680 [==============================] - 1s 142us/step - loss: 0.0746 - acc: 0.9793 - val_loss: 0.6123 - val_acc: 0.8120
Epoch 3/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0515 - acc: 0.9859Epoch 00003: val_loss improved from 0.61231 to 0.60656, saving model to saved_models3/weights.best.ResNet_bs35_ep35.hdf5
6680/6680 [==============================] - 1s 141us/step - loss: 0.0514 - acc: 0.9861 - val_loss: 0.6066 - val_acc: 0.8419
Epoch 4/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.0375 - acc: 0.9908Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0375 - acc: 0.9907 - val_loss: 0.6700 - val_acc: 0.8251
Epoch 5/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.0271 - acc: 0.9938Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0273 - acc: 0.9937 - val_loss: 0.7036 - val_acc: 0.8251
Epoch 6/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0206 - acc: 0.9954Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0204 - acc: 0.9955 - val_loss: 0.6562 - val_acc: 0.8299
Epoch 7/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.0160 - acc: 0.9979Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0160 - acc: 0.9979 - val_loss: 0.7027 - val_acc: 0.8240
Epoch 8/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.0128 - acc: 0.9973Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0128 - acc: 0.9973 - val_loss: 0.7094 - val_acc: 0.8251
Epoch 9/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.0091 - acc: 0.9983Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0091 - acc: 0.9984 - val_loss: 0.7685 - val_acc: 0.8275
Epoch 10/35
6265/6680 [===========================>..] - ETA: 0s - loss: 0.0077 - acc: 0.9981Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0075 - acc: 0.9982 - val_loss: 0.7474 - val_acc: 0.8335
Epoch 11/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0067 - acc: 0.9988Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0068 - acc: 0.9987 - val_loss: 0.7975 - val_acc: 0.8299
Epoch 12/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9992Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0062 - acc: 0.9987 - val_loss: 0.8197 - val_acc: 0.8347
Epoch 13/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0058 - acc: 0.9983Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0057 - acc: 0.9984 - val_loss: 0.8242 - val_acc: 0.8228
Epoch 14/35
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0037 - acc: 0.9991Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0038 - acc: 0.9990 - val_loss: 0.8311 - val_acc: 0.8323
Epoch 15/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9985Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0048 - acc: 0.9985 - val_loss: 0.8865 - val_acc: 0.8240
Epoch 16/35
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9989Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0047 - acc: 0.9990 - val_loss: 0.8887 - val_acc: 0.8347
Epoch 17/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0053 - acc: 0.9984Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0052 - acc: 0.9985 - val_loss: 0.9248 - val_acc: 0.8299
Epoch 18/35
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9986Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 0.9275 - val_acc: 0.8251
Epoch 19/35
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0035 - acc: 0.9989Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 0.8996 - val_acc: 0.8275
Epoch 20/35
6510/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9985Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0043 - acc: 0.9985 - val_loss: 0.9309 - val_acc: 0.8299
Epoch 21/35
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9987Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 0.9384 - val_acc: 0.8240
Epoch 22/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 0.9500 - val_acc: 0.8240
Epoch 23/35
6370/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 0.9678 - val_acc: 0.8263
Epoch 24/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9986Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0035 - acc: 0.9987 - val_loss: 0.9874 - val_acc: 0.8263
Epoch 25/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9984Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.0458 - val_acc: 0.8132
Epoch 26/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9988Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 1.0190 - val_acc: 0.8228
Epoch 27/35
6475/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9988Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 1.0086 - val_acc: 0.8299
Epoch 28/35
6545/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9985Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 1.0147 - val_acc: 0.8287
Epoch 29/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0048 - acc: 0.9985 - val_loss: 1.0259 - val_acc: 0.8311
Epoch 30/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.0707 - val_acc: 0.8395
Epoch 31/35
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9984Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0038 - acc: 0.9985 - val_loss: 1.0625 - val_acc: 0.8347
Epoch 32/35
6510/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 1.1262 - val_acc: 0.8228
Epoch 33/35
6510/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9985Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0050 - acc: 0.9985 - val_loss: 1.0909 - val_acc: 0.8347
Epoch 34/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9988 Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.0839 - val_acc: 0.8395
Epoch 35/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.1221 - val_acc: 0.8335

Batch size=35 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.0412 - acc: 0.9900Epoch 00001: val_loss improved from inf to 0.63494, saving model to saved_models3/weights.best.ResNet_bs35_ep50.hdf5
6680/6680 [==============================] - 1s 141us/step - loss: 0.0416 - acc: 0.9900 - val_loss: 0.6349 - val_acc: 0.8287
Epoch 2/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0271 - acc: 0.9943Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0276 - acc: 0.9942 - val_loss: 0.6757 - val_acc: 0.8299
Epoch 3/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0206 - acc: 0.9968Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0205 - acc: 0.9969 - val_loss: 0.7123 - val_acc: 0.8108
Epoch 4/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0153 - acc: 0.9964Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0152 - acc: 0.9964 - val_loss: 0.7267 - val_acc: 0.8204
Epoch 5/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.0124 - acc: 0.9983Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0125 - acc: 0.9984 - val_loss: 0.7871 - val_acc: 0.8168
Epoch 6/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0101 - acc: 0.9978Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0101 - acc: 0.9978 - val_loss: 0.7250 - val_acc: 0.8228
Epoch 7/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0076 - acc: 0.9989Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0077 - acc: 0.9988 - val_loss: 0.7569 - val_acc: 0.8311
Epoch 8/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0082 - acc: 0.9983Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0081 - acc: 0.9984 - val_loss: 0.7588 - val_acc: 0.8443
Epoch 9/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0073 - acc: 0.9981Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0072 - acc: 0.9982 - val_loss: 0.8089 - val_acc: 0.8287
Epoch 10/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0062 - acc: 0.9988Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0061 - acc: 0.9988 - val_loss: 0.7965 - val_acc: 0.8275
Epoch 11/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0054 - acc: 0.9985 - val_loss: 0.8030 - val_acc: 0.8347
Epoch 12/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9983Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0047 - acc: 0.9984 - val_loss: 0.8322 - val_acc: 0.8287
Epoch 13/50
6300/6680 [===========================>..] - ETA: 0s - loss: 0.0062 - acc: 0.9989Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0059 - acc: 0.9990 - val_loss: 0.8411 - val_acc: 0.8323
Epoch 14/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0053 - acc: 0.9988Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0052 - acc: 0.9988 - val_loss: 0.8733 - val_acc: 0.8335
Epoch 15/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9985Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 0.9026 - val_acc: 0.8311
Epoch 16/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9989Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0048 - acc: 0.9990 - val_loss: 0.9034 - val_acc: 0.8359
Epoch 17/50
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0053 - acc: 0.9986Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0051 - acc: 0.9987 - val_loss: 0.9373 - val_acc: 0.8251
Epoch 18/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0054 - acc: 0.9988Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0052 - acc: 0.9988 - val_loss: 0.9476 - val_acc: 0.8311
Epoch 19/50
6265/6680 [===========================>..] - ETA: 0s - loss: 0.0058 - acc: 0.9987Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0054 - acc: 0.9988 - val_loss: 0.9621 - val_acc: 0.8311
Epoch 20/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0054 - acc: 0.9986Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0053 - acc: 0.9987 - val_loss: 0.9760 - val_acc: 0.8251
Epoch 21/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9988Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 0.9898 - val_acc: 0.8275
Epoch 22/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0032 - acc: 0.9989Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0037 - acc: 0.9988 - val_loss: 0.9913 - val_acc: 0.8275
Epoch 23/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9988Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 1.0225 - val_acc: 0.8192
Epoch 24/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.0019 - val_acc: 0.8251
Epoch 25/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9989Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.0473 - val_acc: 0.8383
Epoch 26/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.0031 - acc: 0.9988Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0037 - acc: 0.9987 - val_loss: 1.0357 - val_acc: 0.8311
Epoch 27/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 1.0419 - val_acc: 0.8299
Epoch 28/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.0035 - acc: 0.9989Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0034 - acc: 0.9990 - val_loss: 1.1074 - val_acc: 0.8371
Epoch 29/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0046 - acc: 0.9985 - val_loss: 1.0703 - val_acc: 0.8251
Epoch 30/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9988Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0050 - acc: 0.9988 - val_loss: 1.0758 - val_acc: 0.8287
Epoch 31/50
6265/6680 [===========================>..] - ETA: 0s - loss: 0.0035 - acc: 0.9986Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 138us/step - loss: 0.0038 - acc: 0.9985 - val_loss: 1.1536 - val_acc: 0.8228
Epoch 32/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0032 - acc: 0.9991Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0043 - acc: 0.9990 - val_loss: 1.0881 - val_acc: 0.8371
Epoch 33/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0033 - acc: 0.9989Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0033 - acc: 0.9990 - val_loss: 1.1016 - val_acc: 0.8299
Epoch 34/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 148us/step - loss: 0.0049 - acc: 0.9985 - val_loss: 1.1210 - val_acc: 0.8359
Epoch 35/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9988Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0052 - acc: 0.9987 - val_loss: 1.1178 - val_acc: 0.8299
Epoch 36/50
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0038 - acc: 0.9990 - val_loss: 1.1435 - val_acc: 0.8311
Epoch 37/50
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0033 - acc: 0.9989Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 1.1200 - val_acc: 0.8251
Epoch 38/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.1427 - val_acc: 0.8323
Epoch 39/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9989Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.1291 - val_acc: 0.8383
Epoch 40/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9986Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 1.1254 - val_acc: 0.8371
Epoch 41/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0042 - acc: 0.9991Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0040 - acc: 0.9991 - val_loss: 1.1342 - val_acc: 0.8359
Epoch 42/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.1426 - val_acc: 0.8275
Epoch 43/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9985Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 1.1492 - val_acc: 0.8347
Epoch 44/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0052 - acc: 0.9988Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0050 - acc: 0.9988 - val_loss: 1.1341 - val_acc: 0.8371
Epoch 45/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9988Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 139us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 1.1608 - val_acc: 0.8383
Epoch 46/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0051 - acc: 0.9988Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0049 - acc: 0.9988 - val_loss: 1.1535 - val_acc: 0.8335
Epoch 47/50
6405/6680 [===========================>..] - ETA: 0s - loss: 0.0033 - acc: 0.9986Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.1879 - val_acc: 0.8347
Epoch 48/50
6475/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.1485 - val_acc: 0.8359
Epoch 49/50
6440/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9983Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0045 - acc: 0.9984 - val_loss: 1.1493 - val_acc: 0.8335
Epoch 50/50
6510/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9988Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1813 - val_acc: 0.8371

Batch size=37 Epoch=25
Train on 6680 samples, validate on 835 samples
Epoch 1/25
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0326 - acc: 0.9924Epoch 00001: val_loss improved from inf to 0.68743, saving model to saved_models3/weights.best.ResNet_bs37_ep25.hdf5
6680/6680 [==============================] - 1s 135us/step - loss: 0.0331 - acc: 0.9925 - val_loss: 0.6874 - val_acc: 0.8275
Epoch 2/25
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0213 - acc: 0.9952Epoch 00002: val_loss improved from 0.68743 to 0.67728, saving model to saved_models3/weights.best.ResNet_bs37_ep25.hdf5
6680/6680 [==============================] - 1s 135us/step - loss: 0.0209 - acc: 0.9954 - val_loss: 0.6773 - val_acc: 0.8168
Epoch 3/25
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0164 - acc: 0.9973Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0161 - acc: 0.9975 - val_loss: 0.6920 - val_acc: 0.8479
Epoch 4/25
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0130 - acc: 0.9969Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0126 - acc: 0.9970 - val_loss: 0.7347 - val_acc: 0.8144
Epoch 5/25
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0086 - acc: 0.9983Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0090 - acc: 0.9982 - val_loss: 0.7600 - val_acc: 0.8120
Epoch 6/25
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0074 - acc: 0.9984Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0076 - acc: 0.9982 - val_loss: 0.7362 - val_acc: 0.8275
Epoch 7/25
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0074 - acc: 0.9981Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0073 - acc: 0.9982 - val_loss: 0.7607 - val_acc: 0.8347
Epoch 8/25
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0058 - acc: 0.9986Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0058 - acc: 0.9985 - val_loss: 0.7961 - val_acc: 0.8275
Epoch 9/25
6660/6680 [============================>.] - ETA: 0s - loss: 0.0054 - acc: 0.9988Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0054 - acc: 0.9988 - val_loss: 0.8090 - val_acc: 0.8216
Epoch 10/25
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0062 - acc: 0.9980Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0060 - acc: 0.9981 - val_loss: 0.8194 - val_acc: 0.8216
Epoch 11/25
6438/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9988Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0050 - acc: 0.9987 - val_loss: 0.8556 - val_acc: 0.8299
Epoch 12/25
6660/6680 [============================>.] - ETA: 0s - loss: 0.0055 - acc: 0.9989Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0055 - acc: 0.9990 - val_loss: 0.8532 - val_acc: 0.8347
Epoch 13/25
6660/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9982Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0047 - acc: 0.9982 - val_loss: 0.8657 - val_acc: 0.8323
Epoch 14/25
6660/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9983Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0039 - acc: 0.9984 - val_loss: 0.8786 - val_acc: 0.8228
Epoch 15/25
6623/6680 [============================>.] - ETA: 0s - loss: 0.0056 - acc: 0.9985Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0056 - acc: 0.9985 - val_loss: 0.9357 - val_acc: 0.8204
Epoch 16/25
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0033 - acc: 0.9989Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0037 - acc: 0.9987 - val_loss: 0.9410 - val_acc: 0.8335
Epoch 17/25
6512/6680 [============================>.] - ETA: 0s - loss: 0.0029 - acc: 0.9988Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0028 - acc: 0.9988 - val_loss: 0.9484 - val_acc: 0.8240
Epoch 18/25
6549/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 0.9807 - val_acc: 0.8311
Epoch 19/25
6549/6680 [============================>.] - ETA: 0s - loss: 0.0027 - acc: 0.9988Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0031 - acc: 0.9987 - val_loss: 0.9920 - val_acc: 0.8228
Epoch 20/25
6512/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9986Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 1.0131 - val_acc: 0.8156
Epoch 21/25
6549/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9985Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 1.0180 - val_acc: 0.8240
Epoch 22/25
6549/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 0.9996 - val_acc: 0.8251
Epoch 23/25
6512/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.0166 - val_acc: 0.8323
Epoch 24/25
6512/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9983Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0044 - acc: 0.9984 - val_loss: 1.0523 - val_acc: 0.8287
Epoch 25/25
6512/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 142us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.0293 - val_acc: 0.8299

Batch size=37 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6549/6680 [============================>.] - ETA: 0s - loss: 0.0198 - acc: 0.9953Epoch 00001: val_loss improved from inf to 0.73685, saving model to saved_models3/weights.best.ResNet_bs37_ep35.hdf5
6680/6680 [==============================] - 1s 141us/step - loss: 0.0201 - acc: 0.9952 - val_loss: 0.7368 - val_acc: 0.8072
Epoch 2/35
6549/6680 [============================>.] - ETA: 0s - loss: 0.0120 - acc: 0.9965Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0119 - acc: 0.9966 - val_loss: 0.7697 - val_acc: 0.8251
Epoch 3/35
6549/6680 [============================>.] - ETA: 0s - loss: 0.0105 - acc: 0.9974Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0103 - acc: 0.9975 - val_loss: 0.7390 - val_acc: 0.8263
Epoch 4/35
6549/6680 [============================>.] - ETA: 0s - loss: 0.0089 - acc: 0.9986Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0090 - acc: 0.9985 - val_loss: 0.7394 - val_acc: 0.8240
Epoch 5/35
6549/6680 [============================>.] - ETA: 0s - loss: 0.0066 - acc: 0.9983Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 140us/step - loss: 0.0075 - acc: 0.9981 - val_loss: 0.7927 - val_acc: 0.8228
Epoch 6/35
6512/6680 [============================>.] - ETA: 0s - loss: 0.0067 - acc: 0.9988Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 141us/step - loss: 0.0069 - acc: 0.9985 - val_loss: 0.8260 - val_acc: 0.8263
Epoch 7/35
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9984Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0061 - acc: 0.9982 - val_loss: 0.8256 - val_acc: 0.8216
Epoch 8/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9987Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0054 - acc: 0.9985 - val_loss: 0.8441 - val_acc: 0.8263
Epoch 9/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9989Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0048 - acc: 0.9988 - val_loss: 0.8894 - val_acc: 0.8240
Epoch 10/35
6438/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9984Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0043 - acc: 0.9985 - val_loss: 0.7931 - val_acc: 0.8335
Epoch 11/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9986Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0038 - acc: 0.9987 - val_loss: 0.8817 - val_acc: 0.8347
Epoch 12/35
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9989Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 0.9138 - val_acc: 0.8144
Epoch 13/35
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9987Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 0.9537 - val_acc: 0.8287
Epoch 14/35
6623/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9989Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0040 - acc: 0.9990 - val_loss: 0.9308 - val_acc: 0.8251
Epoch 15/35
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0047 - acc: 0.9985 - val_loss: 0.9414 - val_acc: 0.8240
Epoch 16/35
6475/6680 [============================>.] - ETA: 0s - loss: 0.0052 - acc: 0.9991Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 132us/step - loss: 0.0051 - acc: 0.9991 - val_loss: 0.9303 - val_acc: 0.8311
Epoch 17/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0036 - acc: 0.9986Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 0.9874 - val_acc: 0.8299
Epoch 18/35
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 0.9847 - val_acc: 0.8347
Epoch 19/35
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 1.0185 - val_acc: 0.8323
Epoch 20/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9987Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 1.0071 - val_acc: 0.8275
Epoch 21/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9987Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 1.0684 - val_acc: 0.8216
Epoch 22/35
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9983Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0041 - acc: 0.9984 - val_loss: 1.0118 - val_acc: 0.8287
Epoch 23/35
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9987Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.0673 - val_acc: 0.8204
Epoch 24/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.0225 - val_acc: 0.8347
Epoch 25/35
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9984Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.0789 - val_acc: 0.8287
Epoch 26/35
6512/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9986Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0050 - acc: 0.9987 - val_loss: 1.0682 - val_acc: 0.8323
Epoch 27/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9988Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.0933 - val_acc: 0.8251
Epoch 28/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9987Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 1.0988 - val_acc: 0.8299
Epoch 29/35
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0035 - acc: 0.9989Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0036 - acc: 0.9988 - val_loss: 1.1008 - val_acc: 0.8299
Epoch 30/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.1175 - val_acc: 0.8263
Epoch 31/35
6475/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 132us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.1128 - val_acc: 0.8287
Epoch 32/35
6623/6680 [============================>.] - ETA: 0s - loss: 0.0033 - acc: 0.9988Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.1077 - val_acc: 0.8311
Epoch 33/35
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.1202 - val_acc: 0.8407
Epoch 34/35
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.1183 - val_acc: 0.8335
Epoch 35/35
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0036 - acc: 0.9987Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 1.1260 - val_acc: 0.8263

Batch size=37 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6623/6680 [============================>.] - ETA: 0s - loss: 0.0142 - acc: 0.9973Epoch 00001: val_loss improved from inf to 0.76251, saving model to saved_models3/weights.best.ResNet_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 136us/step - loss: 0.0142 - acc: 0.9973 - val_loss: 0.7625 - val_acc: 0.8192
Epoch 2/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0095 - acc: 0.9981Epoch 00002: val_loss improved from 0.76251 to 0.71774, saving model to saved_models3/weights.best.ResNet_bs37_ep50.hdf5
6680/6680 [==============================] - 1s 135us/step - loss: 0.0103 - acc: 0.9979 - val_loss: 0.7177 - val_acc: 0.8168
Epoch 3/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0078 - acc: 0.9978Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0076 - acc: 0.9979 - val_loss: 0.7522 - val_acc: 0.8335
Epoch 4/50
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0080 - acc: 0.9981Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0078 - acc: 0.9982 - val_loss: 0.7696 - val_acc: 0.8204
Epoch 5/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0061 - acc: 0.9987Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0075 - acc: 0.9985 - val_loss: 0.7974 - val_acc: 0.8311
Epoch 6/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0052 - acc: 0.9989Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0052 - acc: 0.9988 - val_loss: 0.8255 - val_acc: 0.8084
Epoch 7/50
6623/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9991Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0050 - acc: 0.9991 - val_loss: 0.8289 - val_acc: 0.8359
Epoch 8/50
6623/6680 [============================>.] - ETA: 0s - loss: 0.0052 - acc: 0.9982Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0051 - acc: 0.9982 - val_loss: 0.8849 - val_acc: 0.8347
Epoch 9/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0056 - acc: 0.9991Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0055 - acc: 0.9990 - val_loss: 0.8558 - val_acc: 0.8251
Epoch 10/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 0.8951 - val_acc: 0.8323
Epoch 11/50
6438/6680 [===========================>..] - ETA: 0s - loss: 0.0034 - acc: 0.9984Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0040 - acc: 0.9984 - val_loss: 0.8832 - val_acc: 0.8192
Epoch 12/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9987Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 0.8951 - val_acc: 0.8371
Epoch 13/50
6438/6680 [===========================>..] - ETA: 0s - loss: 0.0037 - acc: 0.9984Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0036 - acc: 0.9985 - val_loss: 0.9310 - val_acc: 0.8168
Epoch 14/50
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9986Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0036 - acc: 0.9987 - val_loss: 0.9645 - val_acc: 0.8216
Epoch 15/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0040 - acc: 0.9990 - val_loss: 0.9709 - val_acc: 0.8299
Epoch 16/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0035 - acc: 0.9986Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.0027 - val_acc: 0.8240
Epoch 17/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0031 - acc: 0.9991Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0034 - acc: 0.9990 - val_loss: 1.0029 - val_acc: 0.8335
Epoch 18/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9986Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0048 - acc: 0.9987 - val_loss: 1.0110 - val_acc: 0.8299
Epoch 19/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0031 - acc: 0.9989Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0036 - acc: 0.9987 - val_loss: 0.9973 - val_acc: 0.8287
Epoch 20/50
6623/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.0710 - val_acc: 0.8204
Epoch 21/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0030 - acc: 0.9987Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0029 - acc: 0.9988 - val_loss: 1.0188 - val_acc: 0.8287
Epoch 22/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0032 - acc: 0.9992Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 1.0491 - val_acc: 0.8251
Epoch 23/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0034 - acc: 0.9984Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0036 - acc: 0.9984 - val_loss: 1.0740 - val_acc: 0.8323
Epoch 24/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9987Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.0605 - val_acc: 0.8311
Epoch 25/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9985Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.0493 - val_acc: 0.8347
Epoch 26/50
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.0886 - val_acc: 0.8347
Epoch 27/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9987Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 1.1156 - val_acc: 0.8407
Epoch 28/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0034 - acc: 0.9991Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0035 - acc: 0.9990 - val_loss: 1.0845 - val_acc: 0.8371
Epoch 29/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1058 - val_acc: 0.8335
Epoch 30/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9989Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0037 - acc: 0.9990 - val_loss: 1.1136 - val_acc: 0.8383
Epoch 31/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.1169 - val_acc: 0.8335
Epoch 32/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0034 - acc: 0.9992Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0047 - acc: 0.9991 - val_loss: 1.1050 - val_acc: 0.8287
Epoch 33/50
6549/6680 [============================>.] - ETA: 0s - loss: 0.0048 - acc: 0.9988Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.1129 - val_acc: 0.8371
Epoch 34/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 1.1301 - val_acc: 0.8311
Epoch 35/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9985Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.1366 - val_acc: 0.8323
Epoch 36/50
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9984Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0047 - acc: 0.9985 - val_loss: 1.1299 - val_acc: 0.8335
Epoch 37/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.1458 - val_acc: 0.8323
Epoch 38/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9984Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 1.1422 - val_acc: 0.8251
Epoch 39/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0022 - acc: 0.9992Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0034 - acc: 0.9990 - val_loss: 1.1293 - val_acc: 0.8419
Epoch 40/50
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0030 - acc: 0.9989Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0034 - acc: 0.9988 - val_loss: 1.1550 - val_acc: 0.8407
Epoch 41/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9984Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0040 - acc: 0.9984 - val_loss: 1.1714 - val_acc: 0.8347
Epoch 42/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9988Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 1.1361 - val_acc: 0.8359
Epoch 43/50
6253/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 1.1735 - val_acc: 0.8347
Epoch 44/50
6364/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9987Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 1.1676 - val_acc: 0.8323
Epoch 45/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 1.1603 - val_acc: 0.8359
Epoch 46/50
6401/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9988Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 132us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.1709 - val_acc: 0.8323
Epoch 47/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9991Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0050 - acc: 0.9990 - val_loss: 1.1700 - val_acc: 0.8359
Epoch 48/50
6327/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9987Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 133us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.2004 - val_acc: 0.8299
Epoch 49/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0023 - acc: 0.9990Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 134us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.1821 - val_acc: 0.8323
Epoch 50/50
6290/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9984Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 135us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 1.1684 - val_acc: 0.8335

Batch size=40 Epoch=25
Train on 6680 samples, validate on 835 samples
Epoch 1/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0108 - acc: 0.9976Epoch 00001: val_loss improved from inf to 0.73717, saving model to saved_models3/weights.best.ResNet_bs40_ep25.hdf5
6680/6680 [==============================] - 1s 126us/step - loss: 0.0104 - acc: 0.9978 - val_loss: 0.7372 - val_acc: 0.8311
Epoch 2/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9986Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0062 - acc: 0.9982 - val_loss: 0.8063 - val_acc: 0.8263
Epoch 3/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0060 - acc: 0.9980Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0060 - acc: 0.9981 - val_loss: 0.7689 - val_acc: 0.8323
Epoch 4/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0058 - acc: 0.9989Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0055 - acc: 0.9990 - val_loss: 0.8289 - val_acc: 0.8383
Epoch 5/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0057 - acc: 0.9985Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 127us/step - loss: 0.0056 - acc: 0.9985 - val_loss: 0.8278 - val_acc: 0.8335
Epoch 6/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 0.8454 - val_acc: 0.8299
Epoch 7/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9989Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0045 - acc: 0.9990 - val_loss: 0.8417 - val_acc: 0.8407
Epoch 8/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0052 - acc: 0.9985Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0051 - acc: 0.9985 - val_loss: 0.8926 - val_acc: 0.8347
Epoch 9/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0054 - acc: 0.9987 - val_loss: 0.8808 - val_acc: 0.8287
Epoch 10/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9987Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 0.9091 - val_acc: 0.8347
Epoch 11/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0033 - acc: 0.9987Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 0.9342 - val_acc: 0.8216
Epoch 12/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9984Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 0.9339 - val_acc: 0.8347
Epoch 13/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 0.9797 - val_acc: 0.8240
Epoch 14/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0031 - acc: 0.9989Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 0.9991 - val_acc: 0.8216
Epoch 15/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0037 - acc: 0.9986Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0035 - acc: 0.9987 - val_loss: 0.9855 - val_acc: 0.8287
Epoch 16/25
6200/6680 [==========================>...] - ETA: 0s - loss: 0.0050 - acc: 0.9984Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0047 - acc: 0.9985 - val_loss: 0.9909 - val_acc: 0.8287
Epoch 17/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0056 - acc: 0.9987Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0056 - acc: 0.9987 - val_loss: 0.9862 - val_acc: 0.8347
Epoch 18/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9983Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0040 - acc: 0.9984 - val_loss: 1.0087 - val_acc: 0.8287
Epoch 19/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9985Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 0.9995 - val_acc: 0.8311
Epoch 20/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9984Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0045 - acc: 0.9984 - val_loss: 1.0517 - val_acc: 0.8263
Epoch 21/25
6360/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9989Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0048 - acc: 0.9990 - val_loss: 1.0567 - val_acc: 0.8311
Epoch 22/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9987Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.0583 - val_acc: 0.8311
Epoch 23/25
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9990Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0049 - acc: 0.9990 - val_loss: 1.0795 - val_acc: 0.8287
Epoch 24/25
6640/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9985Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 1.0794 - val_acc: 0.8347
Epoch 25/25
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0055 - acc: 0.9987Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0058 - acc: 0.9987 - val_loss: 1.0780 - val_acc: 0.8323

Batch size=40 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0076 - acc: 0.9979Epoch 00001: val_loss improved from inf to 0.80388, saving model to saved_models3/weights.best.ResNet_bs40_ep35.hdf5
6680/6680 [==============================] - 1s 127us/step - loss: 0.0086 - acc: 0.9975 - val_loss: 0.8039 - val_acc: 0.8180
Epoch 2/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9988Epoch 00002: val_loss improved from 0.80388 to 0.79296, saving model to saved_models3/weights.best.ResNet_bs40_ep35.hdf5
6680/6680 [==============================] - 1s 127us/step - loss: 0.0049 - acc: 0.9988 - val_loss: 0.7930 - val_acc: 0.8335
Epoch 3/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0056 - acc: 0.9986Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0056 - acc: 0.9987 - val_loss: 0.7946 - val_acc: 0.8275
Epoch 4/35
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9983Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0058 - acc: 0.9982 - val_loss: 0.8023 - val_acc: 0.8251
Epoch 5/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 0.8043 - val_acc: 0.8359
Epoch 6/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9987Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 0.8354 - val_acc: 0.8335
Epoch 7/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0054 - acc: 0.9987Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 0.9094 - val_acc: 0.8263
Epoch 8/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9985Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 127us/step - loss: 0.0037 - acc: 0.9985 - val_loss: 0.9048 - val_acc: 0.8251
Epoch 9/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9990Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0046 - acc: 0.9990 - val_loss: 0.8868 - val_acc: 0.8299
Epoch 10/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0038 - acc: 0.9985 - val_loss: 0.9228 - val_acc: 0.8287
Epoch 11/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 0.9553 - val_acc: 0.8275
Epoch 12/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9989Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 0.9490 - val_acc: 0.8323
Epoch 13/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0053 - acc: 0.9987Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0050 - acc: 0.9988 - val_loss: 0.9520 - val_acc: 0.8335
Epoch 14/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0035 - acc: 0.9986Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 0.9968 - val_acc: 0.8240
Epoch 15/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0032 - acc: 0.9987Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 0.9726 - val_acc: 0.8311
Epoch 16/35
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0042 - acc: 0.9987Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 0.9934 - val_acc: 0.8335
Epoch 17/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9988Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0123 - val_acc: 0.8251
Epoch 18/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9984Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.0188 - val_acc: 0.8371
Epoch 19/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9988Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0038 - acc: 0.9988 - val_loss: 1.0137 - val_acc: 0.8299
Epoch 20/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0264 - val_acc: 0.8335
Epoch 21/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.0637 - val_acc: 0.8359
Epoch 22/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.0752 - val_acc: 0.8216
Epoch 23/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9986Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0036 - acc: 0.9987 - val_loss: 1.0810 - val_acc: 0.8216
Epoch 24/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0026 - acc: 0.9987Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0036 - acc: 0.9982 - val_loss: 1.1024 - val_acc: 0.8263
Epoch 25/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0046 - acc: 0.9985 - val_loss: 1.1003 - val_acc: 0.8287
Epoch 26/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0038 - acc: 0.9987 - val_loss: 1.0903 - val_acc: 0.8359
Epoch 27/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9987Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0046 - acc: 0.9988 - val_loss: 1.0987 - val_acc: 0.8299
Epoch 28/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9988Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 1.1139 - val_acc: 0.8192
Epoch 29/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 1.1074 - val_acc: 0.8275
Epoch 30/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0035 - acc: 0.9989Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0038 - acc: 0.9988 - val_loss: 1.0980 - val_acc: 0.8383
Epoch 31/35
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9989Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0049 - acc: 0.9988 - val_loss: 1.0906 - val_acc: 0.8323
Epoch 32/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9988Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.1301 - val_acc: 0.8335
Epoch 33/35
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9987Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1357 - val_acc: 0.8299
Epoch 34/35
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9987Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 1.1444 - val_acc: 0.8335
Epoch 35/35
6480/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 131us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.1301 - val_acc: 0.8347

Batch size=40 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0058 - acc: 0.9986Epoch 00001: val_loss improved from inf to 0.81031, saving model to saved_models3/weights.best.ResNet_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 126us/step - loss: 0.0065 - acc: 0.9985 - val_loss: 0.8103 - val_acc: 0.8347
Epoch 2/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0058 - acc: 0.9987 - val_loss: 0.8251 - val_acc: 0.8263
Epoch 3/50
6400/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9980Epoch 00003: val_loss improved from 0.81031 to 0.79688, saving model to saved_models3/weights.best.ResNet_bs40_ep50.hdf5
6680/6680 [==============================] - 1s 126us/step - loss: 0.0047 - acc: 0.9981 - val_loss: 0.7969 - val_acc: 0.8311
Epoch 4/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0038 - acc: 0.9987Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0048 - acc: 0.9987 - val_loss: 0.8555 - val_acc: 0.8323
Epoch 5/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9987Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0046 - acc: 0.9985 - val_loss: 0.8406 - val_acc: 0.8287
Epoch 6/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 126us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 0.8918 - val_acc: 0.8204
Epoch 7/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9985Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 0.9074 - val_acc: 0.8287
Epoch 8/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0057 - acc: 0.9989Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0057 - acc: 0.9988 - val_loss: 0.9107 - val_acc: 0.8347
Epoch 9/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9988Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0036 - acc: 0.9988 - val_loss: 0.9490 - val_acc: 0.8275
Epoch 10/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9984Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 0.9256 - val_acc: 0.8299
Epoch 11/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 0.9633 - val_acc: 0.8251
Epoch 12/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 0.9927 - val_acc: 0.8359
Epoch 13/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9987Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 0.9725 - val_acc: 0.8311
Epoch 14/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0037 - acc: 0.9990Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.0220 - val_acc: 0.8251
Epoch 15/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9981Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0042 - acc: 0.9982 - val_loss: 0.9953 - val_acc: 0.8263
Epoch 16/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9987Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.0549 - val_acc: 0.8347
Epoch 17/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9987Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0046 - acc: 0.9988 - val_loss: 1.0134 - val_acc: 0.8359
Epoch 18/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0033 - acc: 0.9988Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0036 - acc: 0.9987 - val_loss: 1.0655 - val_acc: 0.8359
Epoch 19/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0033 - acc: 0.9992Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0035 - acc: 0.9990 - val_loss: 1.1034 - val_acc: 0.8359
Epoch 20/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9985Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.0709 - val_acc: 0.8359
Epoch 21/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0030 - acc: 0.9989Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0046 - acc: 0.9985 - val_loss: 1.0838 - val_acc: 0.8335
Epoch 22/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0044 - acc: 0.9987Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.0821 - val_acc: 0.8251
Epoch 23/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0052 - acc: 0.9989Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0048 - acc: 0.9990 - val_loss: 1.0890 - val_acc: 0.8347
Epoch 24/50
6360/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9984Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 1.0852 - val_acc: 0.8275
Epoch 25/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0034 - acc: 0.9986Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0036 - acc: 0.9985 - val_loss: 1.1274 - val_acc: 0.8359
Epoch 26/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0039 - acc: 0.9984Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0036 - acc: 0.9985 - val_loss: 1.1086 - val_acc: 0.8263
Epoch 27/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0042 - acc: 0.9984Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.0962 - val_acc: 0.8323
Epoch 28/50
6360/6680 [===========================>..] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 123us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.0974 - val_acc: 0.8311
Epoch 29/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9987Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.0957 - val_acc: 0.8359
Epoch 30/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0032 - acc: 0.9987Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0037 - acc: 0.9985 - val_loss: 1.1428 - val_acc: 0.8311
Epoch 31/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0047 - acc: 0.9990 - val_loss: 1.1139 - val_acc: 0.8287
Epoch 32/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0048 - acc: 0.9987Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 1.1197 - val_acc: 0.8347
Epoch 33/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1323 - val_acc: 0.8359
Epoch 34/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.1308 - val_acc: 0.8311
Epoch 35/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9988Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 1.1554 - val_acc: 0.8383
Epoch 36/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9984Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0043 - acc: 0.9985 - val_loss: 1.1325 - val_acc: 0.8347
Epoch 37/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0048 - acc: 0.9988Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0048 - acc: 0.9988 - val_loss: 1.1392 - val_acc: 0.8359
Epoch 38/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9988Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 1.1422 - val_acc: 0.8335
Epoch 39/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 1.1545 - val_acc: 0.8335
Epoch 40/50
6360/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9989Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 123us/step - loss: 0.0044 - acc: 0.9990 - val_loss: 1.1448 - val_acc: 0.8299
Epoch 41/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9989Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.1606 - val_acc: 0.8299
Epoch 42/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0055 - acc: 0.9987Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 123us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 1.1482 - val_acc: 0.8347
Epoch 43/50
6320/6680 [===========================>..] - ETA: 0s - loss: 0.0031 - acc: 0.9989Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0035 - acc: 0.9988 - val_loss: 1.1467 - val_acc: 0.8275
Epoch 44/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0042 - acc: 0.9990Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0047 - acc: 0.9990 - val_loss: 1.1490 - val_acc: 0.8347
Epoch 45/50
6200/6680 [==========================>...] - ETA: 0s - loss: 0.0054 - acc: 0.9987Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 125us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 1.1517 - val_acc: 0.8287
Epoch 46/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1644 - val_acc: 0.8323
Epoch 47/50
6280/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9987Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.1522 - val_acc: 0.8359
Epoch 48/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0048 - acc: 0.9988 - val_loss: 1.1585 - val_acc: 0.8359
Epoch 49/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0041 - acc: 0.9992Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0048 - acc: 0.9990 - val_loss: 1.1489 - val_acc: 0.8383
Epoch 50/50
6240/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9987Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 124us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.1496 - val_acc: 0.8335

Batch size=64 Epoch=25
Train on 6680 samples, validate on 835 samples
Epoch 1/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9983Epoch 00001: val_loss improved from inf to 0.88103, saving model to saved_models3/weights.best.ResNet_bs64_ep25.hdf5
6680/6680 [==============================] - 1s 89us/step - loss: 0.0048 - acc: 0.9984 - val_loss: 0.8810 - val_acc: 0.8287
Epoch 2/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00002: val_loss improved from 0.88103 to 0.86433, saving model to saved_models3/weights.best.ResNet_bs64_ep25.hdf5
6680/6680 [==============================] - 1s 89us/step - loss: 0.0046 - acc: 0.9990 - val_loss: 0.8643 - val_acc: 0.8287
Epoch 3/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9989Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 0.8650 - val_acc: 0.8359
Epoch 4/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00004: val_loss improved from 0.86433 to 0.86284, saving model to saved_models3/weights.best.ResNet_bs64_ep25.hdf5
6680/6680 [==============================] - 1s 89us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 0.8628 - val_acc: 0.8299
Epoch 5/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 0.9286 - val_acc: 0.8228
Epoch 6/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9983Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0050 - acc: 0.9984 - val_loss: 0.8897 - val_acc: 0.8251
Epoch 7/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0025 - acc: 0.9991Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 0.9256 - val_acc: 0.8359
Epoch 8/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0025 - acc: 0.9989Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0037 - acc: 0.9987 - val_loss: 0.9814 - val_acc: 0.8323
Epoch 9/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0031 - acc: 0.9988Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 0.9467 - val_acc: 0.8323
Epoch 10/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9988Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 0.9696 - val_acc: 0.8263
Epoch 11/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 0.9480 - val_acc: 0.8347
Epoch 12/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 0.9868 - val_acc: 0.8323
Epoch 13/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9988Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0036 - acc: 0.9988 - val_loss: 1.0207 - val_acc: 0.8323
Epoch 14/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9985Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 0.9974 - val_acc: 0.8275
Epoch 15/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9985Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 1.0057 - val_acc: 0.8275
Epoch 16/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0640 - val_acc: 0.8287
Epoch 17/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9986Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 1.0650 - val_acc: 0.8263
Epoch 18/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0034 - acc: 0.9989Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0656 - val_acc: 0.8168
Epoch 19/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9988Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0035 - acc: 0.9988 - val_loss: 1.0248 - val_acc: 0.8335
Epoch 20/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.0464 - val_acc: 0.8347
Epoch 21/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.0585 - val_acc: 0.8347
Epoch 22/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9989Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0583 - val_acc: 0.8311
Epoch 23/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9988  Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 1.1181 - val_acc: 0.8251
Epoch 24/25
6464/6680 [============================>.] - ETA: 0s - loss: 0.0032 - acc: 0.9991Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0034 - acc: 0.9990 - val_loss: 1.0509 - val_acc: 0.8299
Epoch 25/25
6528/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9983Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0044 - acc: 0.9984 - val_loss: 1.0717 - val_acc: 0.8347

Batch size=64 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9988  Epoch 00001: val_loss improved from inf to 0.87991, saving model to saved_models3/weights.best.ResNet_bs64_ep35.hdf5
6680/6680 [==============================] - 1s 89us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 0.8799 - val_acc: 0.8383
Epoch 2/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0048 - acc: 0.9986Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 0.8959 - val_acc: 0.8347
Epoch 3/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9983Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0037 - acc: 0.9984 - val_loss: 0.8818 - val_acc: 0.8347
Epoch 4/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9988Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 0.9509 - val_acc: 0.8287
Epoch 5/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0034 - acc: 0.9989Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 0.9423 - val_acc: 0.8263
Epoch 6/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9986Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 0.9511 - val_acc: 0.8359
Epoch 7/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0048 - acc: 0.9988Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0046 - acc: 0.9988 - val_loss: 0.9902 - val_acc: 0.8263
Epoch 8/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9986Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 0.9793 - val_acc: 0.8263
Epoch 9/35
6592/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.0159 - val_acc: 0.8275
Epoch 10/35
6528/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9989Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0045 - acc: 0.9990 - val_loss: 1.0142 - val_acc: 0.8335
Epoch 11/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9988  Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 1.0106 - val_acc: 0.8371
Epoch 12/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9988Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 1.0243 - val_acc: 0.8311
Epoch 13/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0035 - acc: 0.9988Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 1.0250 - val_acc: 0.8323
Epoch 14/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9985Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9984 - val_loss: 1.0267 - val_acc: 0.8371
Epoch 15/35
6528/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.0757 - val_acc: 0.8359
Epoch 16/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0039 - acc: 0.9990 - val_loss: 1.0430 - val_acc: 0.8371
Epoch 17/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9989Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0046 - acc: 0.9988 - val_loss: 1.0543 - val_acc: 0.8383
Epoch 18/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9989Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0037 - acc: 0.9990 - val_loss: 1.0554 - val_acc: 0.8323
Epoch 19/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9986Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0036 - acc: 0.9987 - val_loss: 1.0523 - val_acc: 0.8371
Epoch 20/35
6528/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 1.0741 - val_acc: 0.8263
Epoch 21/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9988Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 86us/step - loss: 0.0038 - acc: 0.9988 - val_loss: 1.0691 - val_acc: 0.8395
Epoch 22/35
6528/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.0950 - val_acc: 0.8323
Epoch 23/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.0761 - val_acc: 0.8311
Epoch 24/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9989 Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 1.0821 - val_acc: 0.8347
Epoch 25/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9991 Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9991 - val_loss: 1.0882 - val_acc: 0.8311
Epoch 26/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9991Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9990 - val_loss: 1.0878 - val_acc: 0.8371
Epoch 27/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9985Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9985 - val_loss: 1.1159 - val_acc: 0.8263
Epoch 28/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0038 - acc: 0.9987 - val_loss: 1.1045 - val_acc: 0.8383
Epoch 29/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9988Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9988 - val_loss: 1.0874 - val_acc: 0.8383
Epoch 30/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 1.0989 - val_acc: 0.8395
Epoch 31/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9983Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9984 - val_loss: 1.1087 - val_acc: 0.8383
Epoch 32/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.1008 - val_acc: 0.8311
Epoch 33/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9986Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.0954 - val_acc: 0.8359
Epoch 34/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0046 - acc: 0.9985 - val_loss: 1.0991 - val_acc: 0.8419
Epoch 35/35
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0040 - acc: 0.9990 - val_loss: 1.1156 - val_acc: 0.8347

Batch size=64 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9988Epoch 00001: val_loss improved from inf to 0.93283, saving model to saved_models3/weights.best.ResNet_bs64_ep50.hdf5
6680/6680 [==============================] - 1s 90us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 0.9328 - val_acc: 0.8311
Epoch 2/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9989Epoch 00002: val_loss improved from 0.93283 to 0.91360, saving model to saved_models3/weights.best.ResNet_bs64_ep50.hdf5
6680/6680 [==============================] - 1s 91us/step - loss: 0.0039 - acc: 0.9990 - val_loss: 0.9136 - val_acc: 0.8311
Epoch 3/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0052 - acc: 0.9988Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0050 - acc: 0.9988 - val_loss: 0.9582 - val_acc: 0.8263
Epoch 4/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988  Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 0.9269 - val_acc: 0.8335
Epoch 5/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9989Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 0.9460 - val_acc: 0.8323
Epoch 6/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.0013 - val_acc: 0.8299
Epoch 7/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9985Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0035 - acc: 0.9985 - val_loss: 0.9837 - val_acc: 0.8359
Epoch 8/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 0.9974 - val_acc: 0.8240
Epoch 9/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9985Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0048 - acc: 0.9985 - val_loss: 0.9789 - val_acc: 0.8335
Epoch 10/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9991Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0049 - acc: 0.9991 - val_loss: 1.0252 - val_acc: 0.8371
Epoch 11/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9986 Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0035 - acc: 0.9987 - val_loss: 1.0105 - val_acc: 0.8275
Epoch 12/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0031 - acc: 0.9988Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0035 - acc: 0.9987 - val_loss: 1.0039 - val_acc: 0.8347
Epoch 13/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0029 - acc: 0.9991Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0044 - acc: 0.9988 - val_loss: 1.0660 - val_acc: 0.8323
Epoch 14/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0025 - acc: 0.9992 Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0038 - acc: 0.9990 - val_loss: 1.0445 - val_acc: 0.8323
Epoch 15/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0036 - acc: 0.9988Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0039 - acc: 0.9987 - val_loss: 1.0358 - val_acc: 0.8287
Epoch 16/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9988Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.0603 - val_acc: 0.8347
Epoch 17/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9986Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.0503 - val_acc: 0.8359
Epoch 18/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9988Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0048 - acc: 0.9988 - val_loss: 1.0584 - val_acc: 0.8431
Epoch 19/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0034 - acc: 0.9986   Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 1.0955 - val_acc: 0.8383
Epoch 20/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9989 Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.0851 - val_acc: 0.8347
Epoch 21/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9989Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9990 - val_loss: 1.0992 - val_acc: 0.8311
Epoch 22/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.0696 - val_acc: 0.8347
Epoch 23/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9986Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.0945 - val_acc: 0.8311
Epoch 24/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0037 - acc: 0.9985Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0036 - acc: 0.9985 - val_loss: 1.0882 - val_acc: 0.8299
Epoch 25/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.0977 - val_acc: 0.8371
Epoch 26/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9985Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9984 - val_loss: 1.0964 - val_acc: 0.8335
Epoch 27/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9990 - val_loss: 1.1041 - val_acc: 0.8383
Epoch 28/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9989Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0044 - acc: 0.9990 - val_loss: 1.0819 - val_acc: 0.8347
Epoch 29/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9985 Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0048 - acc: 0.9985 - val_loss: 1.0925 - val_acc: 0.8347
Epoch 30/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9983Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0044 - acc: 0.9984 - val_loss: 1.1030 - val_acc: 0.8323
Epoch 31/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9988Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0040 - acc: 0.9988 - val_loss: 1.1165 - val_acc: 0.8407
Epoch 32/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.1095 - val_acc: 0.8371
Epoch 33/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0033 - acc: 0.9988Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 1.1279 - val_acc: 0.8335
Epoch 34/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0046 - acc: 0.9987 - val_loss: 1.1017 - val_acc: 0.8383
Epoch 35/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0043 - acc: 0.9985Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0042 - acc: 0.9985 - val_loss: 1.1132 - val_acc: 0.8383
Epoch 36/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9987 - val_loss: 1.1072 - val_acc: 0.8347
Epoch 37/50
6528/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 1.1212 - val_acc: 0.8371
Epoch 38/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9987 - val_loss: 1.1192 - val_acc: 0.8371
Epoch 39/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9988Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9987 - val_loss: 1.1143 - val_acc: 0.8371
Epoch 40/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9989Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0040 - acc: 0.9990 - val_loss: 1.0998 - val_acc: 0.8395
Epoch 41/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9988Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.1230 - val_acc: 0.8323
Epoch 42/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9989Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0045 - acc: 0.9990 - val_loss: 1.1361 - val_acc: 0.8383
Epoch 43/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0033 - acc: 0.9991Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0039 - acc: 0.9990 - val_loss: 1.1207 - val_acc: 0.8419
Epoch 44/50
6528/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0041 - acc: 0.9988 - val_loss: 1.1273 - val_acc: 0.8311
Epoch 45/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9988Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 1.1272 - val_acc: 0.8299
Epoch 46/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9991Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0038 - acc: 0.9991 - val_loss: 1.1509 - val_acc: 0.8275
Epoch 47/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0032 - acc: 0.9991Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 1s 88us/step - loss: 0.0043 - acc: 0.9990 - val_loss: 1.1262 - val_acc: 0.8395
Epoch 48/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9991Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0039 - acc: 0.9991 - val_loss: 1.1215 - val_acc: 0.8383
Epoch 49/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9991Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 1s 89us/step - loss: 0.0044 - acc: 0.9990 - val_loss: 1.1473 - val_acc: 0.8299
Epoch 50/50
6464/6680 [============================>.] - ETA: 0s - loss: 0.0039 - acc: 0.9988Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 1s 87us/step - loss: 0.0040 - acc: 0.9987 - val_loss: 1.1230 - val_acc: 0.8323
In [34]:
pd.DataFrame(fitingdict_ResNet)
Out[34]:
Batch_Size Epochs Test_Accuracy
0 35 25 80.263158
1 35 35 82.296651
2 35 50 81.937799
3 37 25 81.937799
4 37 35 82.057416
5 37 50 80.861244
6 40 25 82.416268
7 40 35 81.818182
8 40 50 81.937799
9 64 25 82.177033
10 64 35 81.339713
11 64 50 81.937799
In [35]:
#take largest testaccuracy's batch size and epochs
ind=fitingdict_ResNet['Test_Accuracy'].index(max(fitingdict_ResNet['Test_Accuracy']))
bs=fitingdict_ResNet['Batch_Size'][ind]
ep=fitingdict_ResNet['Epochs'][ind]

#LOAD the model with Best validation loss 
ResNet_model.load_weights('saved_models3/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')
### TODO: Calculate classification accuracy on the test dataset.
# get index of predicted dog breed for each image in test set
ResNet_predictions = [np.argmax(ResNet_model.predict(np.expand_dims(feature, axis=0))) for feature in test_Resnet50]
# report test accuracy
test_accuracy = 100*np.sum(np.array(ResNet_predictions)==np.argmax(test_targets, axis=1))/len(ResNet_predictions)
print('Test accuracy: %.4f%%' % test_accuracy)
Test accuracy: 82.4163%

lets do with Xception model

In [26]:
### TODO: Obtain bottleneck features from another pre-trained CNN.
bottleneck_features = np.load('/data/bottleneck_features/DogXceptionData.npz')
train_Xception = bottleneck_features['train']
valid_Xception = bottleneck_features['valid']
test_Xception = bottleneck_features['test']

(IMPLEMENTATION) Model Architecture

Create a CNN to classify dog breed. At the end of your code cell block, summarize the layers of your model by executing the line:

    <your model's name>.summary()

Question 5: Outline the steps you took to get to your final CNN architecture and your reasoning at each step. Describe why you think the architecture is suitable for the current problem.

Answer: The below architecture using Xception model is most suitable for current problem as it gave me Test accuracy of 86.8421% which is higher then other model i tested. We can see that in ResNet-50 the Maximum Test accuracy is 82.4163% on batch_size=40 and epoch=25 and VGG-16 is 53.1100% on batch_size=35 and epoch=40 and in Xception model the Minimum test accuracy is starts from 84.330144%. thats the reason i go with Xception model. I used with BatchNormalization as Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change. This slows down the training by requiring lower learning rates and careful parameter initialization, and makes it notoriously hard to train models with saturating nonlinearities. We refer to this phenomenon as internal covariate shift, and address the problem by normalizing layer inputs.

In [27]:
### TODO: Define your architecture.
from keras.layers import Conv2D, MaxPooling2D, GlobalAveragePooling2D,BatchNormalization
from keras.layers import Dropout, Flatten, Dense, Activation
from keras.models import Sequential
from keras.callbacks import ModelCheckpoint  

Xception_model=Sequential()
Xception_model.add(GlobalAveragePooling2D(input_shape=train_Xception.shape[1:]))
Xception_model.add(BatchNormalization())

# let's add a fully-connected layer
Xception_model.add(Dropout(0.5))
Xception_model.add( Dense(1024, activation='relu'))
Xception_model.add( Dropout(0.5))
# and a logistic layer -- let's say we have NUM_CLASSES classes
Xception_model.add( Dense(len(dog_names), activation='softmax'))

Xception_model.summary()
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
global_average_pooling2d_3 ( (None, 2048)              0         
_________________________________________________________________
batch_normalization_1 (Batch (None, 2048)              8192      
_________________________________________________________________
dropout_1 (Dropout)          (None, 2048)              0         
_________________________________________________________________
dense_3 (Dense)              (None, 1024)              2098176   
_________________________________________________________________
dropout_2 (Dropout)          (None, 1024)              0         
_________________________________________________________________
dense_4 (Dense)              (None, 133)               136325    
=================================================================
Total params: 2,242,693
Trainable params: 2,238,597
Non-trainable params: 4,096
_________________________________________________________________

(IMPLEMENTATION) Compile the Model

In [28]:
### TODO: Compile the model
Xception_model.compile(loss="categorical_crossentropy",optimizer="rmsprop",metrics=["accuracy"])

(IMPLEMENTATION) Train the Model

Train your model in the code cell below. Use model checkpointing to save the model that attains the best validation loss.

You are welcome to augment the training data, but this is not a requirement.

In [55]:
### TODO: Train the model.
from sklearn.model_selection import GridSearchCV
# defining the grid search parameters
batch_size = [35,36,37,40,41]
epochs = [35,37,40,50,55]

fitingdict={'Batch_Size':[], 
            'Epochs':[],
            'Test_Accuracy':[]}

for bs in batch_size:
    for ep in epochs:
        checkpointer = ModelCheckpoint(filepath='saved_models2/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5', 
                               verbose=1, save_best_only=True)
        print("\nBatch size={0} Epoch={1}".format(bs,ep))
        Xception_model.fit(train_Xception, train_targets,validation_data=(valid_Xception, valid_targets),
                          epochs=ep , batch_size=bs,
                          callbacks=[checkpointer],verbose=1)

        #LOAD the model with Best validation loss
        Xception_model.load_weights('saved_models2/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')

        
        Xception_predictions = [np.argmax(Xception_model.predict(np.expand_dims(feature, axis=0))) for feature in test_Xception]
        test_accuracy = 100*np.sum(np.array(Xception_predictions)==np.argmax(test_targets, axis=1))/len(Xception_predictions)
        fitingdict['Batch_Size'].append(bs)
        fitingdict['Epochs'].append(ep)
        fitingdict['Test_Accuracy'].append(test_accuracy)
Batch size=35 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.1983 - acc: 0.9708Epoch 00001: val_loss improved from inf to 1.46264, saving model to saved_models2/weights.best.ResNet_bs35_ep35.hdf5
6680/6680 [==============================] - 4s 558us/step - loss: 0.1990 - acc: 0.9707 - val_loss: 1.4626 - val_acc: 0.8587
Epoch 2/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2076 - acc: 0.9701Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2091 - acc: 0.9699 - val_loss: 1.5414 - val_acc: 0.8479
Epoch 3/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2040 - acc: 0.9677Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 565us/step - loss: 0.2032 - acc: 0.9678 - val_loss: 1.5532 - val_acc: 0.8455
Epoch 4/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.1886 - acc: 0.9702Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 548us/step - loss: 0.1905 - acc: 0.9702 - val_loss: 1.5364 - val_acc: 0.8599
Epoch 5/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2214 - acc: 0.9686Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2214 - acc: 0.9686 - val_loss: 1.5839 - val_acc: 0.8431
Epoch 6/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2250 - acc: 0.9675Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2228 - acc: 0.9678 - val_loss: 1.5875 - val_acc: 0.8491
Epoch 7/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2215 - acc: 0.9687Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2210 - acc: 0.9687 - val_loss: 1.5775 - val_acc: 0.8479
Epoch 8/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2353 - acc: 0.9672Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 548us/step - loss: 0.2337 - acc: 0.9674 - val_loss: 1.5295 - val_acc: 0.8635
Epoch 9/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2365 - acc: 0.9649Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2396 - acc: 0.9650 - val_loss: 1.5912 - val_acc: 0.8563
Epoch 10/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2046 - acc: 0.9708Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2043 - acc: 0.9708 - val_loss: 1.6751 - val_acc: 0.8491
Epoch 11/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2118 - acc: 0.9681Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2098 - acc: 0.9684 - val_loss: 1.6789 - val_acc: 0.8539
Epoch 12/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2341 - acc: 0.9669Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2338 - acc: 0.9668 - val_loss: 1.6250 - val_acc: 0.8539
Epoch 13/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2284 - acc: 0.9693Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2277 - acc: 0.9693 - val_loss: 1.6745 - val_acc: 0.8383
Epoch 14/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2067 - acc: 0.9691Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.2037 - acc: 0.9696 - val_loss: 1.6129 - val_acc: 0.8539
Epoch 15/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2221 - acc: 0.9691Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2221 - acc: 0.9693 - val_loss: 1.6107 - val_acc: 0.8563
Epoch 16/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2156 - acc: 0.9705Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2158 - acc: 0.9705 - val_loss: 1.7286 - val_acc: 0.8395
Epoch 17/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2373 - acc: 0.9686Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2387 - acc: 0.9686 - val_loss: 1.6144 - val_acc: 0.8539
Epoch 18/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2206 - acc: 0.9687Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2193 - acc: 0.9686 - val_loss: 1.5646 - val_acc: 0.8515
Epoch 19/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2287 - acc: 0.9673Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2288 - acc: 0.9674 - val_loss: 1.5570 - val_acc: 0.8515
Epoch 20/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2382 - acc: 0.9667Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 554us/step - loss: 0.2354 - acc: 0.9671 - val_loss: 1.6206 - val_acc: 0.8491
Epoch 21/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2268 - acc: 0.9682Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2269 - acc: 0.9680 - val_loss: 1.5614 - val_acc: 0.8539
Epoch 22/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2028 - acc: 0.9698Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2034 - acc: 0.9698 - val_loss: 1.6625 - val_acc: 0.8527
Epoch 23/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2289 - acc: 0.9690Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 548us/step - loss: 0.2269 - acc: 0.9692 - val_loss: 1.6965 - val_acc: 0.8503
Epoch 24/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2574 - acc: 0.9643Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 550us/step - loss: 0.2549 - acc: 0.9647 - val_loss: 1.7081 - val_acc: 0.8491
Epoch 25/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2560 - acc: 0.9684Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2553 - acc: 0.9683 - val_loss: 1.7107 - val_acc: 0.8551
Epoch 26/35
6580/6680 [============================>.] - ETA: 0s - loss: 0.2156 - acc: 0.9690Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2155 - acc: 0.9692 - val_loss: 1.7609 - val_acc: 0.8539
Epoch 27/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2194 - acc: 0.9698Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2208 - acc: 0.9698 - val_loss: 1.7678 - val_acc: 0.8407
Epoch 28/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2147 - acc: 0.9708Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2162 - acc: 0.9707 - val_loss: 1.7648 - val_acc: 0.8431
Epoch 29/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2105 - acc: 0.9723Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2096 - acc: 0.9725 - val_loss: 1.7228 - val_acc: 0.8455
Epoch 30/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2411 - acc: 0.9695Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2424 - acc: 0.9695 - val_loss: 1.6352 - val_acc: 0.8491
Epoch 31/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2312 - acc: 0.9689Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2317 - acc: 0.9689 - val_loss: 1.6527 - val_acc: 0.8443
Epoch 32/35
6615/6680 [============================>.] - ETA: 0s - loss: 0.2396 - acc: 0.9684Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 554us/step - loss: 0.2386 - acc: 0.9686 - val_loss: 1.7082 - val_acc: 0.8479
Epoch 33/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2295 - acc: 0.9704Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.2303 - acc: 0.9702 - val_loss: 1.6698 - val_acc: 0.8587
Epoch 34/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.2157 - acc: 0.9722Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 560us/step - loss: 0.2148 - acc: 0.9723 - val_loss: 1.6363 - val_acc: 0.8551
Epoch 35/35
6650/6680 [============================>.] - ETA: 0s - loss: 0.1835 - acc: 0.9747Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.1839 - acc: 0.9746 - val_loss: 1.7155 - val_acc: 0.8479

Batch size=35 Epoch=37
Train on 6680 samples, validate on 835 samples
Epoch 1/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2034 - acc: 0.9688Epoch 00001: val_loss improved from inf to 1.49988, saving model to saved_models2/weights.best.ResNet_bs35_ep37.hdf5
6680/6680 [==============================] - 4s 549us/step - loss: 0.2048 - acc: 0.9686 - val_loss: 1.4999 - val_acc: 0.8467
Epoch 2/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2080 - acc: 0.9692Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2071 - acc: 0.9690 - val_loss: 1.5362 - val_acc: 0.8491
Epoch 3/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.1951 - acc: 0.9704Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1967 - acc: 0.9702 - val_loss: 1.6042 - val_acc: 0.8431
Epoch 4/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2176 - acc: 0.9684Epoch 00004: val_loss improved from 1.49988 to 1.47475, saving model to saved_models2/weights.best.ResNet_bs35_ep37.hdf5
6680/6680 [==============================] - 4s 533us/step - loss: 0.2204 - acc: 0.9680 - val_loss: 1.4748 - val_acc: 0.8479
Epoch 5/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2302 - acc: 0.9657Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2330 - acc: 0.9656 - val_loss: 1.5861 - val_acc: 0.8371
Epoch 6/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2440 - acc: 0.9661Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2422 - acc: 0.9663 - val_loss: 1.5851 - val_acc: 0.8443
Epoch 7/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2183 - acc: 0.9705Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2192 - acc: 0.9704 - val_loss: 1.6422 - val_acc: 0.8431
Epoch 8/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2278 - acc: 0.9663Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 549us/step - loss: 0.2276 - acc: 0.9660 - val_loss: 1.6035 - val_acc: 0.8431
Epoch 9/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2083 - acc: 0.9690Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2114 - acc: 0.9689 - val_loss: 1.5379 - val_acc: 0.8479
Epoch 10/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2075 - acc: 0.9690Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2076 - acc: 0.9689 - val_loss: 1.6530 - val_acc: 0.8419
Epoch 11/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2309 - acc: 0.9642Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 549us/step - loss: 0.2299 - acc: 0.9644 - val_loss: 1.6663 - val_acc: 0.8539
Epoch 12/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2173 - acc: 0.9704Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 551us/step - loss: 0.2177 - acc: 0.9705 - val_loss: 1.5863 - val_acc: 0.8479
Epoch 13/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2146 - acc: 0.9690Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2201 - acc: 0.9684 - val_loss: 1.6451 - val_acc: 0.8467
Epoch 14/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2316 - acc: 0.9678Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 550us/step - loss: 0.2326 - acc: 0.9678 - val_loss: 1.6160 - val_acc: 0.8515
Epoch 15/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2086 - acc: 0.9717Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2070 - acc: 0.9719 - val_loss: 1.6887 - val_acc: 0.8443
Epoch 16/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2209 - acc: 0.9690Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2228 - acc: 0.9684 - val_loss: 1.6448 - val_acc: 0.8503
Epoch 17/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2307 - acc: 0.9681Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2314 - acc: 0.9680 - val_loss: 1.6715 - val_acc: 0.8479
Epoch 18/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2274 - acc: 0.9681Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.2272 - acc: 0.9680 - val_loss: 1.6892 - val_acc: 0.8539
Epoch 19/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2228 - acc: 0.9681Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2223 - acc: 0.9681 - val_loss: 1.6204 - val_acc: 0.8491
Epoch 20/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2435 - acc: 0.9660Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2427 - acc: 0.9660 - val_loss: 1.7267 - val_acc: 0.8527
Epoch 21/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2355 - acc: 0.9679Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 551us/step - loss: 0.2349 - acc: 0.9678 - val_loss: 1.7047 - val_acc: 0.8455
Epoch 22/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.1936 - acc: 0.9717Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1942 - acc: 0.9719 - val_loss: 1.6707 - val_acc: 0.8479
Epoch 23/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2089 - acc: 0.9702Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2103 - acc: 0.9701 - val_loss: 1.6694 - val_acc: 0.8491
Epoch 24/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2125 - acc: 0.9701Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2124 - acc: 0.9701 - val_loss: 1.6934 - val_acc: 0.8395
Epoch 25/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2319 - acc: 0.9693Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2345 - acc: 0.9693 - val_loss: 1.6656 - val_acc: 0.8503
Epoch 26/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.1993 - acc: 0.9736Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1976 - acc: 0.9737 - val_loss: 1.7276 - val_acc: 0.8515
Epoch 27/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2080 - acc: 0.9701Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2090 - acc: 0.9698 - val_loss: 1.7145 - val_acc: 0.8467
Epoch 28/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2293 - acc: 0.9692Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2281 - acc: 0.9693 - val_loss: 1.8158 - val_acc: 0.8491
Epoch 29/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2177 - acc: 0.9689Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2191 - acc: 0.9689 - val_loss: 1.7366 - val_acc: 0.8491
Epoch 30/37
6545/6680 [============================>.] - ETA: 0s - loss: 0.2335 - acc: 0.9716Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2313 - acc: 0.9720 - val_loss: 1.7351 - val_acc: 0.8467
Epoch 31/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.1734 - acc: 0.9755Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1741 - acc: 0.9756 - val_loss: 1.7981 - val_acc: 0.8479
Epoch 32/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.2093 - acc: 0.9710Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2100 - acc: 0.9711 - val_loss: 1.6974 - val_acc: 0.8503
Epoch 33/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.2102 - acc: 0.9723Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 554us/step - loss: 0.2109 - acc: 0.9722 - val_loss: 1.7001 - val_acc: 0.8479
Epoch 34/37
6650/6680 [============================>.] - ETA: 0s - loss: 0.1960 - acc: 0.9752Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1951 - acc: 0.9753 - val_loss: 1.7649 - val_acc: 0.8455
Epoch 35/37
6580/6680 [============================>.] - ETA: 0s - loss: 0.1914 - acc: 0.9723Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1891 - acc: 0.9726 - val_loss: 1.6935 - val_acc: 0.8503
Epoch 36/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2145 - acc: 0.9713Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2172 - acc: 0.9713 - val_loss: 1.6966 - val_acc: 0.8479
Epoch 37/37
6615/6680 [============================>.] - ETA: 0s - loss: 0.2002 - acc: 0.9743Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1998 - acc: 0.9744 - val_loss: 1.7340 - val_acc: 0.8419

Batch size=35 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2050 - acc: 0.9698Epoch 00001: val_loss improved from inf to 1.57961, saving model to saved_models2/weights.best.ResNet_bs35_ep40.hdf5
6680/6680 [==============================] - 4s 540us/step - loss: 0.2051 - acc: 0.9698 - val_loss: 1.5796 - val_acc: 0.8527
Epoch 2/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2181 - acc: 0.9662Epoch 00002: val_loss improved from 1.57961 to 1.57918, saving model to saved_models2/weights.best.ResNet_bs35_ep40.hdf5
6680/6680 [==============================] - 4s 541us/step - loss: 0.2183 - acc: 0.9662 - val_loss: 1.5792 - val_acc: 0.8515
Epoch 3/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2174 - acc: 0.9682Epoch 00003: val_loss improved from 1.57918 to 1.55264, saving model to saved_models2/weights.best.ResNet_bs35_ep40.hdf5
6680/6680 [==============================] - 4s 545us/step - loss: 0.2185 - acc: 0.9683 - val_loss: 1.5526 - val_acc: 0.8479
Epoch 4/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.1973 - acc: 0.9707Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1983 - acc: 0.9708 - val_loss: 1.5899 - val_acc: 0.8455
Epoch 5/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2116 - acc: 0.9690Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2111 - acc: 0.9689 - val_loss: 1.6002 - val_acc: 0.8503
Epoch 6/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2186 - acc: 0.9690Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2173 - acc: 0.9690 - val_loss: 1.7026 - val_acc: 0.8443
Epoch 7/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.1951 - acc: 0.9698Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.1949 - acc: 0.9698 - val_loss: 1.6093 - val_acc: 0.8443
Epoch 8/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2294 - acc: 0.9661Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.2266 - acc: 0.9663 - val_loss: 1.6390 - val_acc: 0.8479
Epoch 9/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2156 - acc: 0.9698Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 556us/step - loss: 0.2147 - acc: 0.9699 - val_loss: 1.7127 - val_acc: 0.8443
Epoch 10/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.1985 - acc: 0.9711Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.1980 - acc: 0.9711 - val_loss: 1.6772 - val_acc: 0.8491
Epoch 11/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2006 - acc: 0.9684Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1978 - acc: 0.9687 - val_loss: 1.6577 - val_acc: 0.8587
Epoch 12/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2267 - acc: 0.9674Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2259 - acc: 0.9674 - val_loss: 1.7310 - val_acc: 0.8503
Epoch 13/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2166 - acc: 0.9711Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2167 - acc: 0.9710 - val_loss: 1.6735 - val_acc: 0.8515
Epoch 14/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2109 - acc: 0.9725Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 555us/step - loss: 0.2105 - acc: 0.9726 - val_loss: 1.6766 - val_acc: 0.8527
Epoch 15/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2174 - acc: 0.9701Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2181 - acc: 0.9701 - val_loss: 1.6891 - val_acc: 0.8539
Epoch 16/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2128 - acc: 0.9672Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.2145 - acc: 0.9671 - val_loss: 1.7557 - val_acc: 0.8491
Epoch 17/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.1981 - acc: 0.9698Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1975 - acc: 0.9698 - val_loss: 1.7375 - val_acc: 0.8539
Epoch 18/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2200 - acc: 0.9696Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2204 - acc: 0.9695 - val_loss: 1.7566 - val_acc: 0.8515
Epoch 19/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2073 - acc: 0.9717Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2093 - acc: 0.9714 - val_loss: 1.7231 - val_acc: 0.8551
Epoch 20/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2118 - acc: 0.9716Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2114 - acc: 0.9714 - val_loss: 1.6856 - val_acc: 0.8479
Epoch 21/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2253 - acc: 0.9707Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2313 - acc: 0.9698 - val_loss: 1.7512 - val_acc: 0.8419
Epoch 22/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2037 - acc: 0.9731Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2044 - acc: 0.9731 - val_loss: 1.8039 - val_acc: 0.8443
Epoch 23/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2255 - acc: 0.9714Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2263 - acc: 0.9713 - val_loss: 1.8122 - val_acc: 0.8419
Epoch 24/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2358 - acc: 0.9692Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2358 - acc: 0.9692 - val_loss: 1.8351 - val_acc: 0.8395
Epoch 25/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2113 - acc: 0.9716Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2148 - acc: 0.9716 - val_loss: 1.7378 - val_acc: 0.8539
Epoch 26/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2262 - acc: 0.9716Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 548us/step - loss: 0.2240 - acc: 0.9719 - val_loss: 1.6965 - val_acc: 0.8491
Epoch 27/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2210 - acc: 0.9705Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2214 - acc: 0.9704 - val_loss: 1.7100 - val_acc: 0.8479
Epoch 28/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2120 - acc: 0.9698Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 549us/step - loss: 0.2177 - acc: 0.9695 - val_loss: 1.6952 - val_acc: 0.8551
Epoch 29/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.1829 - acc: 0.9743Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 551us/step - loss: 0.1807 - acc: 0.9746 - val_loss: 1.7109 - val_acc: 0.8491
Epoch 30/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.1996 - acc: 0.9738Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2052 - acc: 0.9735 - val_loss: 1.7434 - val_acc: 0.8563
Epoch 31/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.1937 - acc: 0.9745Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2014 - acc: 0.9737 - val_loss: 1.7621 - val_acc: 0.8503
Epoch 32/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2028 - acc: 0.9726Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2003 - acc: 0.9728 - val_loss: 1.8297 - val_acc: 0.8479
Epoch 33/40
6650/6680 [============================>.] - ETA: 0s - loss: 0.2345 - acc: 0.9687Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2337 - acc: 0.9687 - val_loss: 1.8895 - val_acc: 0.8419
Epoch 34/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2124 - acc: 0.9716Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2118 - acc: 0.9716 - val_loss: 1.8027 - val_acc: 0.8503
Epoch 35/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2141 - acc: 0.9723Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2115 - acc: 0.9726 - val_loss: 1.7901 - val_acc: 0.8479
Epoch 36/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2277 - acc: 0.9699Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2255 - acc: 0.9702 - val_loss: 1.7508 - val_acc: 0.8503
Epoch 37/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2198 - acc: 0.9749Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 548us/step - loss: 0.2185 - acc: 0.9750 - val_loss: 1.7222 - val_acc: 0.8539
Epoch 38/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2210 - acc: 0.9726Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2211 - acc: 0.9726 - val_loss: 1.6103 - val_acc: 0.8671
Epoch 39/40
6580/6680 [============================>.] - ETA: 0s - loss: 0.2491 - acc: 0.9690Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2551 - acc: 0.9687 - val_loss: 1.7978 - val_acc: 0.8455
Epoch 40/40
6615/6680 [============================>.] - ETA: 0s - loss: 0.2161 - acc: 0.9728Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2177 - acc: 0.9725 - val_loss: 1.7624 - val_acc: 0.8551

Batch size=35 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2373 - acc: 0.9670Epoch 00001: val_loss improved from inf to 1.61396, saving model to saved_models2/weights.best.ResNet_bs35_ep50.hdf5
6680/6680 [==============================] - 4s 546us/step - loss: 0.2353 - acc: 0.9672 - val_loss: 1.6140 - val_acc: 0.8479
Epoch 2/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2221 - acc: 0.9680Epoch 00002: val_loss improved from 1.61396 to 1.58716, saving model to saved_models2/weights.best.ResNet_bs35_ep50.hdf5
6680/6680 [==============================] - 4s 550us/step - loss: 0.2211 - acc: 0.9681 - val_loss: 1.5872 - val_acc: 0.8515
Epoch 3/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2156 - acc: 0.9678Epoch 00003: val_loss improved from 1.58716 to 1.53811, saving model to saved_models2/weights.best.ResNet_bs35_ep50.hdf5
6680/6680 [==============================] - 4s 543us/step - loss: 0.2147 - acc: 0.9680 - val_loss: 1.5381 - val_acc: 0.8527
Epoch 4/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2352 - acc: 0.9682Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2326 - acc: 0.9684 - val_loss: 1.5989 - val_acc: 0.8491
Epoch 5/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2225 - acc: 0.9687Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2202 - acc: 0.9690 - val_loss: 1.6043 - val_acc: 0.8479
Epoch 6/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2194 - acc: 0.9693Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2203 - acc: 0.9693 - val_loss: 1.5950 - val_acc: 0.8491
Epoch 7/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2419 - acc: 0.9657Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2438 - acc: 0.9651 - val_loss: 1.5617 - val_acc: 0.8515
Epoch 8/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1951 - acc: 0.9717Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1970 - acc: 0.9719 - val_loss: 1.6485 - val_acc: 0.8563
Epoch 9/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2196 - acc: 0.9698Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2187 - acc: 0.9699 - val_loss: 1.6241 - val_acc: 0.8443
Epoch 10/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2509 - acc: 0.9662Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2498 - acc: 0.9663 - val_loss: 1.5574 - val_acc: 0.8563
Epoch 11/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1924 - acc: 0.9733Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1924 - acc: 0.9734 - val_loss: 1.5948 - val_acc: 0.8563
Epoch 12/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2180 - acc: 0.9687Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2177 - acc: 0.9684 - val_loss: 1.6430 - val_acc: 0.8551
Epoch 13/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2280 - acc: 0.9681Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2271 - acc: 0.9683 - val_loss: 1.5841 - val_acc: 0.8515
Epoch 14/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2185 - acc: 0.9702Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2176 - acc: 0.9704 - val_loss: 1.5892 - val_acc: 0.8623
Epoch 15/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2331 - acc: 0.9677Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2322 - acc: 0.9678 - val_loss: 1.5724 - val_acc: 0.8587
Epoch 16/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2091 - acc: 0.9717Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2082 - acc: 0.9716 - val_loss: 1.6042 - val_acc: 0.8599
Epoch 17/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2041 - acc: 0.9729Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 557us/step - loss: 0.2040 - acc: 0.9729 - val_loss: 1.6621 - val_acc: 0.8539
Epoch 18/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2191 - acc: 0.9698Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2208 - acc: 0.9696 - val_loss: 1.6563 - val_acc: 0.8479
Epoch 19/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.1909 - acc: 0.9737Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1901 - acc: 0.9738 - val_loss: 1.5439 - val_acc: 0.8599
Epoch 20/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2361 - acc: 0.9689Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 558us/step - loss: 0.2350 - acc: 0.9690 - val_loss: 1.6316 - val_acc: 0.8563
Epoch 21/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1697 - acc: 0.9748Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1695 - acc: 0.9750 - val_loss: 1.7533 - val_acc: 0.8455
Epoch 22/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1951 - acc: 0.9739Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1932 - acc: 0.9741 - val_loss: 1.7192 - val_acc: 0.8563
Epoch 23/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2083 - acc: 0.9714Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2079 - acc: 0.9716 - val_loss: 1.7421 - val_acc: 0.8431
Epoch 24/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2171 - acc: 0.9695Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2155 - acc: 0.9695 - val_loss: 1.6734 - val_acc: 0.8467
Epoch 25/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2226 - acc: 0.9722Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 552us/step - loss: 0.2216 - acc: 0.9723 - val_loss: 1.7285 - val_acc: 0.8431
Epoch 26/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.1990 - acc: 0.9726Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1981 - acc: 0.9728 - val_loss: 1.7738 - val_acc: 0.8551
Epoch 27/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2141 - acc: 0.9720Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2130 - acc: 0.9719 - val_loss: 1.8278 - val_acc: 0.8431
Epoch 28/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2176 - acc: 0.9711Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2174 - acc: 0.9708 - val_loss: 1.7967 - val_acc: 0.8503
Epoch 29/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2201 - acc: 0.9710Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2202 - acc: 0.9710 - val_loss: 1.6576 - val_acc: 0.8587
Epoch 30/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2104 - acc: 0.9717Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2148 - acc: 0.9713 - val_loss: 1.7897 - val_acc: 0.8455
Epoch 31/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2067 - acc: 0.9722Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2090 - acc: 0.9719 - val_loss: 1.7685 - val_acc: 0.8455
Epoch 32/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2238 - acc: 0.9695Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2267 - acc: 0.9693 - val_loss: 1.6748 - val_acc: 0.8515
Epoch 33/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2188 - acc: 0.9711Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2180 - acc: 0.9711 - val_loss: 1.7607 - val_acc: 0.8443
Epoch 34/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2052 - acc: 0.9729Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2044 - acc: 0.9729 - val_loss: 1.8621 - val_acc: 0.8431
Epoch 35/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2085 - acc: 0.9711Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2089 - acc: 0.9710 - val_loss: 1.6788 - val_acc: 0.8551
Epoch 36/50
6545/6680 [============================>.] - ETA: 0s - loss: 0.2065 - acc: 0.9739Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2092 - acc: 0.9735 - val_loss: 1.7225 - val_acc: 0.8419
Epoch 37/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1997 - acc: 0.9746Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1998 - acc: 0.9746 - val_loss: 1.6924 - val_acc: 0.8575
Epoch 38/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2274 - acc: 0.9723Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2255 - acc: 0.9725 - val_loss: 1.7085 - val_acc: 0.8527
Epoch 39/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1970 - acc: 0.9719Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1947 - acc: 0.9722 - val_loss: 1.6784 - val_acc: 0.8587
Epoch 40/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.1997 - acc: 0.9737Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1986 - acc: 0.9738 - val_loss: 1.6745 - val_acc: 0.8575
Epoch 41/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.1916 - acc: 0.9749Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1900 - acc: 0.9750 - val_loss: 1.6702 - val_acc: 0.8599
Epoch 42/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.1986 - acc: 0.9745Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2000 - acc: 0.9744 - val_loss: 1.7238 - val_acc: 0.8563
Epoch 43/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.1906 - acc: 0.9743Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1921 - acc: 0.9743 - val_loss: 1.5852 - val_acc: 0.8623
Epoch 44/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2217 - acc: 0.9704Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2229 - acc: 0.9704 - val_loss: 1.7437 - val_acc: 0.8575
Epoch 45/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2064 - acc: 0.9732Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2069 - acc: 0.9732 - val_loss: 1.7420 - val_acc: 0.8527
Epoch 46/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2207 - acc: 0.9736Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2174 - acc: 0.9740 - val_loss: 1.6796 - val_acc: 0.8455
Epoch 47/50
6580/6680 [============================>.] - ETA: 0s - loss: 0.2010 - acc: 0.9751Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2011 - acc: 0.9751 - val_loss: 1.7013 - val_acc: 0.8551
Epoch 48/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.1765 - acc: 0.9764Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1748 - acc: 0.9766 - val_loss: 1.7327 - val_acc: 0.8491
Epoch 49/50
6650/6680 [============================>.] - ETA: 0s - loss: 0.2010 - acc: 0.9756Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 550us/step - loss: 0.2027 - acc: 0.9754 - val_loss: 1.7723 - val_acc: 0.8563
Epoch 50/50
6615/6680 [============================>.] - ETA: 0s - loss: 0.2294 - acc: 0.9699Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2282 - acc: 0.9699 - val_loss: 1.6563 - val_acc: 0.8611

Batch size=35 Epoch=55
Train on 6680 samples, validate on 835 samples
Epoch 1/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2337 - acc: 0.9672Epoch 00001: val_loss improved from inf to 1.53496, saving model to saved_models2/weights.best.ResNet_bs35_ep55.hdf5
6680/6680 [==============================] - 4s 543us/step - loss: 0.2318 - acc: 0.9671 - val_loss: 1.5350 - val_acc: 0.8527
Epoch 2/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2314 - acc: 0.9675Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2299 - acc: 0.9675 - val_loss: 1.5563 - val_acc: 0.8551
Epoch 3/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2377 - acc: 0.9666Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2368 - acc: 0.9668 - val_loss: 1.6695 - val_acc: 0.8599
Epoch 4/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2163 - acc: 0.9699Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2172 - acc: 0.9695 - val_loss: 1.6477 - val_acc: 0.8479
Epoch 5/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2156 - acc: 0.9696Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2187 - acc: 0.9693 - val_loss: 1.6535 - val_acc: 0.8587
Epoch 6/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2113 - acc: 0.9686Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2113 - acc: 0.9683 - val_loss: 1.7155 - val_acc: 0.8407
Epoch 7/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2318 - acc: 0.9676Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2310 - acc: 0.9678 - val_loss: 1.6509 - val_acc: 0.8491
Epoch 8/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2347 - acc: 0.9682Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.2328 - acc: 0.9684 - val_loss: 1.5887 - val_acc: 0.8467
Epoch 9/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2383 - acc: 0.9679Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2370 - acc: 0.9681 - val_loss: 1.6649 - val_acc: 0.8515
Epoch 10/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2182 - acc: 0.9687Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2208 - acc: 0.9687 - val_loss: 1.7140 - val_acc: 0.8479
Epoch 11/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1808 - acc: 0.9743Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1809 - acc: 0.9744 - val_loss: 1.7025 - val_acc: 0.8431
Epoch 12/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1903 - acc: 0.9729Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1902 - acc: 0.9729 - val_loss: 1.6464 - val_acc: 0.8575
Epoch 13/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2066 - acc: 0.9714Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2065 - acc: 0.9716 - val_loss: 1.7272 - val_acc: 0.8551
Epoch 14/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.1981 - acc: 0.9726Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2004 - acc: 0.9725 - val_loss: 1.6762 - val_acc: 0.8479
Epoch 15/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2080 - acc: 0.9690Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.2129 - acc: 0.9687 - val_loss: 1.6263 - val_acc: 0.8587
Epoch 16/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2490 - acc: 0.9685Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2516 - acc: 0.9686 - val_loss: 1.6783 - val_acc: 0.8635
Epoch 17/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2528 - acc: 0.9676Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 550us/step - loss: 0.2521 - acc: 0.9675 - val_loss: 1.6556 - val_acc: 0.8539
Epoch 18/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1925 - acc: 0.9749Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1996 - acc: 0.9743 - val_loss: 1.6879 - val_acc: 0.8527
Epoch 19/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1925 - acc: 0.9714Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1940 - acc: 0.9714 - val_loss: 1.7877 - val_acc: 0.8443
Epoch 20/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.1928 - acc: 0.9731Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1910 - acc: 0.9734 - val_loss: 1.7319 - val_acc: 0.8431
Epoch 21/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2235 - acc: 0.9680Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 552us/step - loss: 0.2225 - acc: 0.9681 - val_loss: 1.6924 - val_acc: 0.8563
Epoch 22/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2057 - acc: 0.9731Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2052 - acc: 0.9731 - val_loss: 1.7560 - val_acc: 0.8491
Epoch 23/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2144 - acc: 0.9701Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2150 - acc: 0.9699 - val_loss: 1.7489 - val_acc: 0.8515
Epoch 24/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1932 - acc: 0.9740Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1905 - acc: 0.9744 - val_loss: 1.7383 - val_acc: 0.8503
Epoch 25/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2164 - acc: 0.9711Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2154 - acc: 0.9713 - val_loss: 1.6781 - val_acc: 0.8479
Epoch 26/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2083 - acc: 0.9738Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2081 - acc: 0.9738 - val_loss: 1.6529 - val_acc: 0.8539
Epoch 27/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1862 - acc: 0.9723Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1895 - acc: 0.9720 - val_loss: 1.7055 - val_acc: 0.8491
Epoch 28/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2164 - acc: 0.9702Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2176 - acc: 0.9702 - val_loss: 1.7171 - val_acc: 0.8407
Epoch 29/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1941 - acc: 0.9749Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1939 - acc: 0.9747 - val_loss: 1.7295 - val_acc: 0.8407
Epoch 30/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2381 - acc: 0.9693Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2375 - acc: 0.9693 - val_loss: 1.7486 - val_acc: 0.8431
Epoch 31/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2279 - acc: 0.9708Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2279 - acc: 0.9708 - val_loss: 1.6858 - val_acc: 0.8491
Epoch 32/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2050 - acc: 0.9725Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.2042 - acc: 0.9726 - val_loss: 1.8060 - val_acc: 0.8407
Epoch 33/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1888 - acc: 0.9754Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1863 - acc: 0.9756 - val_loss: 1.8319 - val_acc: 0.8371
Epoch 34/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1844 - acc: 0.9752Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1862 - acc: 0.9750 - val_loss: 1.7339 - val_acc: 0.8467
Epoch 35/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2277 - acc: 0.9722Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2267 - acc: 0.9723 - val_loss: 1.7243 - val_acc: 0.8563
Epoch 36/55
6545/6680 [============================>.] - ETA: 0s - loss: 0.2134 - acc: 0.9719Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2113 - acc: 0.9719 - val_loss: 1.7754 - val_acc: 0.8539
Epoch 37/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.1994 - acc: 0.9749Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1976 - acc: 0.9750 - val_loss: 1.7738 - val_acc: 0.8527
Epoch 38/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2227 - acc: 0.9729Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2229 - acc: 0.9729 - val_loss: 1.6982 - val_acc: 0.8563
Epoch 39/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2243 - acc: 0.9704Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2243 - acc: 0.9705 - val_loss: 1.7920 - val_acc: 0.8503
Epoch 40/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1941 - acc: 0.9743Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1919 - acc: 0.9746 - val_loss: 1.7830 - val_acc: 0.8479
Epoch 41/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2062 - acc: 0.9737Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2061 - acc: 0.9737 - val_loss: 1.8822 - val_acc: 0.8419
Epoch 42/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2008 - acc: 0.9751Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2003 - acc: 0.9753 - val_loss: 1.8787 - val_acc: 0.8467
Epoch 43/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2279 - acc: 0.9723Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 556us/step - loss: 0.2309 - acc: 0.9722 - val_loss: 1.8503 - val_acc: 0.8515
Epoch 44/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1870 - acc: 0.9751Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1843 - acc: 0.9754 - val_loss: 1.7806 - val_acc: 0.8479
Epoch 45/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1990 - acc: 0.9734Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1982 - acc: 0.9735 - val_loss: 1.7717 - val_acc: 0.8503
Epoch 46/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2177 - acc: 0.9717Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2167 - acc: 0.9719 - val_loss: 1.8158 - val_acc: 0.8491
Epoch 47/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.2193 - acc: 0.9729Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2185 - acc: 0.9729 - val_loss: 1.8537 - val_acc: 0.8503
Epoch 48/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.2004 - acc: 0.9736Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.2005 - acc: 0.9735 - val_loss: 1.8280 - val_acc: 0.8527
Epoch 49/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.1678 - acc: 0.9767Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1671 - acc: 0.9768 - val_loss: 1.7521 - val_acc: 0.8635
Epoch 50/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1952 - acc: 0.9739Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.1947 - acc: 0.9738 - val_loss: 1.7072 - val_acc: 0.8539
Epoch 51/55
6615/6680 [============================>.] - ETA: 0s - loss: 0.2219 - acc: 0.9741Epoch 00051: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2291 - acc: 0.9737 - val_loss: 1.8146 - val_acc: 0.8467
Epoch 52/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1993 - acc: 0.9737Epoch 00052: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1999 - acc: 0.9737 - val_loss: 1.8970 - val_acc: 0.8431
Epoch 53/55
6580/6680 [============================>.] - ETA: 0s - loss: 0.1869 - acc: 0.9748Epoch 00053: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1893 - acc: 0.9743 - val_loss: 1.8256 - val_acc: 0.8467
Epoch 54/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1895 - acc: 0.9761Epoch 00054: val_loss did not improve
6680/6680 [==============================] - 4s 551us/step - loss: 0.1892 - acc: 0.9760 - val_loss: 1.8524 - val_acc: 0.8479
Epoch 55/55
6650/6680 [============================>.] - ETA: 0s - loss: 0.1889 - acc: 0.9746Epoch 00055: val_loss did not improve
6680/6680 [==============================] - 4s 550us/step - loss: 0.1881 - acc: 0.9747 - val_loss: 1.8245 - val_acc: 0.8467

Batch size=36 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2251 - acc: 0.9706Epoch 00001: val_loss improved from inf to 1.64562, saving model to saved_models2/weights.best.ResNet_bs36_ep35.hdf5
6680/6680 [==============================] - 4s 538us/step - loss: 0.2259 - acc: 0.9705 - val_loss: 1.6456 - val_acc: 0.8563
Epoch 2/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2313 - acc: 0.9671Epoch 00002: val_loss improved from 1.64562 to 1.62733, saving model to saved_models2/weights.best.ResNet_bs36_ep35.hdf5
6680/6680 [==============================] - 4s 553us/step - loss: 0.2297 - acc: 0.9672 - val_loss: 1.6273 - val_acc: 0.8527
Epoch 3/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2041 - acc: 0.9713Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2035 - acc: 0.9714 - val_loss: 1.6556 - val_acc: 0.8527
Epoch 4/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2205 - acc: 0.9683Epoch 00004: val_loss improved from 1.62733 to 1.59287, saving model to saved_models2/weights.best.ResNet_bs36_ep35.hdf5
6680/6680 [==============================] - 4s 553us/step - loss: 0.2221 - acc: 0.9683 - val_loss: 1.5929 - val_acc: 0.8515
Epoch 5/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2127 - acc: 0.9673Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2125 - acc: 0.9672 - val_loss: 1.6604 - val_acc: 0.8515
Epoch 6/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.1778 - acc: 0.9730Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1809 - acc: 0.9728 - val_loss: 1.6150 - val_acc: 0.8491
Epoch 7/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2187 - acc: 0.9683Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2174 - acc: 0.9684 - val_loss: 1.6720 - val_acc: 0.8515
Epoch 8/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.1820 - acc: 0.9718Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1825 - acc: 0.9717 - val_loss: 1.6518 - val_acc: 0.8455
Epoch 9/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2453 - acc: 0.9691Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2448 - acc: 0.9690 - val_loss: 1.6650 - val_acc: 0.8467
Epoch 10/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2311 - acc: 0.9689Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2297 - acc: 0.9687 - val_loss: 1.6412 - val_acc: 0.8503
Epoch 11/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2110 - acc: 0.9699Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2172 - acc: 0.9693 - val_loss: 1.6268 - val_acc: 0.8479
Epoch 12/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2024 - acc: 0.9734Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2022 - acc: 0.9734 - val_loss: 1.6712 - val_acc: 0.8455
Epoch 13/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2068 - acc: 0.9731Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2090 - acc: 0.9728 - val_loss: 1.7154 - val_acc: 0.8527
Epoch 14/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2143 - acc: 0.9710Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2126 - acc: 0.9713 - val_loss: 1.6685 - val_acc: 0.8515
Epoch 15/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2199 - acc: 0.9681Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2203 - acc: 0.9681 - val_loss: 1.6442 - val_acc: 0.8527
Epoch 16/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2012 - acc: 0.9710Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2022 - acc: 0.9710 - val_loss: 1.6515 - val_acc: 0.8515
Epoch 17/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2096 - acc: 0.9721Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2090 - acc: 0.9722 - val_loss: 1.6546 - val_acc: 0.8503
Epoch 18/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2136 - acc: 0.9706Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2143 - acc: 0.9707 - val_loss: 1.6965 - val_acc: 0.8467
Epoch 19/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2161 - acc: 0.9701Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2191 - acc: 0.9701 - val_loss: 1.7219 - val_acc: 0.8503
Epoch 20/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2328 - acc: 0.9716Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2336 - acc: 0.9714 - val_loss: 1.7442 - val_acc: 0.8503
Epoch 21/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2102 - acc: 0.9700Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2121 - acc: 0.9698 - val_loss: 1.7989 - val_acc: 0.8431
Epoch 22/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.1966 - acc: 0.9736Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1966 - acc: 0.9735 - val_loss: 1.7029 - val_acc: 0.8575
Epoch 23/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.1824 - acc: 0.9740Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1818 - acc: 0.9741 - val_loss: 1.6775 - val_acc: 0.8527
Epoch 24/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.2191 - acc: 0.9715Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2214 - acc: 0.9713 - val_loss: 1.6912 - val_acc: 0.8551
Epoch 25/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2172 - acc: 0.9719Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2166 - acc: 0.9720 - val_loss: 1.7433 - val_acc: 0.8527
Epoch 26/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2229 - acc: 0.9706Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2212 - acc: 0.9705 - val_loss: 1.7523 - val_acc: 0.8431
Epoch 27/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2189 - acc: 0.9704Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2199 - acc: 0.9704 - val_loss: 1.7139 - val_acc: 0.8551
Epoch 28/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.1723 - acc: 0.9765Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1706 - acc: 0.9765 - val_loss: 1.7937 - val_acc: 0.8479
Epoch 29/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.1738 - acc: 0.9758Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1723 - acc: 0.9760 - val_loss: 1.7498 - val_acc: 0.8515
Epoch 30/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2110 - acc: 0.9751Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2104 - acc: 0.9751 - val_loss: 1.7236 - val_acc: 0.8515
Epoch 31/35
6624/6680 [============================>.] - ETA: 0s - loss: 0.1849 - acc: 0.9736Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1898 - acc: 0.9731 - val_loss: 1.6944 - val_acc: 0.8527
Epoch 32/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.1787 - acc: 0.9750Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1833 - acc: 0.9746 - val_loss: 1.7182 - val_acc: 0.8479
Epoch 33/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.1928 - acc: 0.9752Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1939 - acc: 0.9751 - val_loss: 1.8333 - val_acc: 0.8503
Epoch 34/35
6588/6680 [============================>.] - ETA: 0s - loss: 0.2112 - acc: 0.9712Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2098 - acc: 0.9714 - val_loss: 1.7831 - val_acc: 0.8491
Epoch 35/35
6660/6680 [============================>.] - ETA: 0s - loss: 0.2124 - acc: 0.9734Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2118 - acc: 0.9735 - val_loss: 1.8777 - val_acc: 0.8455

Batch size=36 Epoch=37
Train on 6680 samples, validate on 835 samples
Epoch 1/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2058 - acc: 0.9722Epoch 00001: val_loss improved from inf to 1.70843, saving model to saved_models2/weights.best.ResNet_bs36_ep37.hdf5
6680/6680 [==============================] - 4s 553us/step - loss: 0.2059 - acc: 0.9720 - val_loss: 1.7084 - val_acc: 0.8503
Epoch 2/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2373 - acc: 0.9698Epoch 00002: val_loss improved from 1.70843 to 1.68580, saving model to saved_models2/weights.best.ResNet_bs36_ep37.hdf5
6680/6680 [==============================] - 4s 549us/step - loss: 0.2355 - acc: 0.9701 - val_loss: 1.6858 - val_acc: 0.8455
Epoch 3/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2329 - acc: 0.9681Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2309 - acc: 0.9684 - val_loss: 1.7367 - val_acc: 0.8467
Epoch 4/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.1982 - acc: 0.9707Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.1972 - acc: 0.9707 - val_loss: 1.7250 - val_acc: 0.8503
Epoch 5/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2357 - acc: 0.9675Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2337 - acc: 0.9678 - val_loss: 1.6995 - val_acc: 0.8503
Epoch 6/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2482 - acc: 0.9678Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2485 - acc: 0.9680 - val_loss: 1.7817 - val_acc: 0.8395
Epoch 7/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.1971 - acc: 0.9743Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 549us/step - loss: 0.1966 - acc: 0.9744 - val_loss: 1.7229 - val_acc: 0.8515
Epoch 8/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2249 - acc: 0.9683Epoch 00008: val_loss improved from 1.68580 to 1.63297, saving model to saved_models2/weights.best.ResNet_bs36_ep37.hdf5
6680/6680 [==============================] - 4s 552us/step - loss: 0.2242 - acc: 0.9684 - val_loss: 1.6330 - val_acc: 0.8575
Epoch 9/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.1799 - acc: 0.9733Epoch 00009: val_loss improved from 1.63297 to 1.61080, saving model to saved_models2/weights.best.ResNet_bs36_ep37.hdf5
6680/6680 [==============================] - 4s 549us/step - loss: 0.1874 - acc: 0.9723 - val_loss: 1.6108 - val_acc: 0.8527
Epoch 10/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2255 - acc: 0.9698Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2272 - acc: 0.9699 - val_loss: 1.7514 - val_acc: 0.8455
Epoch 11/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2106 - acc: 0.9716Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2100 - acc: 0.9717 - val_loss: 1.6597 - val_acc: 0.8527
Epoch 12/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.1951 - acc: 0.9746Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1946 - acc: 0.9747 - val_loss: 1.7412 - val_acc: 0.8491
Epoch 13/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2120 - acc: 0.9698Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2135 - acc: 0.9696 - val_loss: 1.6672 - val_acc: 0.8503
Epoch 14/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.1911 - acc: 0.9701Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1902 - acc: 0.9702 - val_loss: 1.7309 - val_acc: 0.8503
Epoch 15/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2127 - acc: 0.9701Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2127 - acc: 0.9701 - val_loss: 1.7519 - val_acc: 0.8575
Epoch 16/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2133 - acc: 0.9680Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2129 - acc: 0.9680 - val_loss: 1.7439 - val_acc: 0.8479
Epoch 17/37
6552/6680 [============================>.] - ETA: 0s - loss: 0.2508 - acc: 0.9666Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2488 - acc: 0.9668 - val_loss: 1.6651 - val_acc: 0.8527
Epoch 18/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2223 - acc: 0.9677Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2192 - acc: 0.9681 - val_loss: 1.7171 - val_acc: 0.8539
Epoch 19/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2151 - acc: 0.9731Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2134 - acc: 0.9734 - val_loss: 1.6873 - val_acc: 0.8539
Epoch 20/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.1995 - acc: 0.9740Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.1978 - acc: 0.9743 - val_loss: 1.7397 - val_acc: 0.8503
Epoch 21/37
6552/6680 [============================>.] - ETA: 0s - loss: 0.1927 - acc: 0.9750Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1896 - acc: 0.9753 - val_loss: 1.6959 - val_acc: 0.8527
Epoch 22/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2141 - acc: 0.9740Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2132 - acc: 0.9741 - val_loss: 1.7483 - val_acc: 0.8431
Epoch 23/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.1734 - acc: 0.9766Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1745 - acc: 0.9762 - val_loss: 1.8066 - val_acc: 0.8431
Epoch 24/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.1942 - acc: 0.9740Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1936 - acc: 0.9741 - val_loss: 1.7419 - val_acc: 0.8527
Epoch 25/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2100 - acc: 0.9724Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2097 - acc: 0.9725 - val_loss: 1.8478 - val_acc: 0.8443
Epoch 26/37
6624/6680 [============================>.] - ETA: 0s - loss: 0.2128 - acc: 0.9731Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2112 - acc: 0.9732 - val_loss: 1.7536 - val_acc: 0.8383
Epoch 27/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2277 - acc: 0.9701Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2324 - acc: 0.9699 - val_loss: 1.8146 - val_acc: 0.8455
Epoch 28/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.1935 - acc: 0.9739Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1961 - acc: 0.9737 - val_loss: 1.7656 - val_acc: 0.8479
Epoch 29/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2214 - acc: 0.9722Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2208 - acc: 0.9723 - val_loss: 1.8015 - val_acc: 0.8431
Epoch 30/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2132 - acc: 0.9739Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2126 - acc: 0.9740 - val_loss: 1.7189 - val_acc: 0.8587
Epoch 31/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2182 - acc: 0.9725Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2176 - acc: 0.9726 - val_loss: 1.7318 - val_acc: 0.8527
Epoch 32/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.2011 - acc: 0.9727Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2034 - acc: 0.9726 - val_loss: 1.7111 - val_acc: 0.8599
Epoch 33/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.1904 - acc: 0.9765Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1909 - acc: 0.9763 - val_loss: 1.8571 - val_acc: 0.8479
Epoch 34/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.1981 - acc: 0.9757Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1975 - acc: 0.9757 - val_loss: 1.8084 - val_acc: 0.8527
Epoch 35/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.2103 - acc: 0.9730Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2098 - acc: 0.9729 - val_loss: 1.7654 - val_acc: 0.8467
Epoch 36/37
6660/6680 [============================>.] - ETA: 0s - loss: 0.1870 - acc: 0.9779Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1865 - acc: 0.9780 - val_loss: 1.7981 - val_acc: 0.8431
Epoch 37/37
6588/6680 [============================>.] - ETA: 0s - loss: 0.1937 - acc: 0.9768Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1938 - acc: 0.9765 - val_loss: 1.7574 - val_acc: 0.8563

Batch size=36 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2235 - acc: 0.9681Epoch 00001: val_loss improved from inf to 1.71629, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 554us/step - loss: 0.2234 - acc: 0.9681 - val_loss: 1.7163 - val_acc: 0.8527
Epoch 2/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2102 - acc: 0.9703Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2111 - acc: 0.9701 - val_loss: 1.7657 - val_acc: 0.8503
Epoch 3/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2106 - acc: 0.9721Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2113 - acc: 0.9720 - val_loss: 1.7317 - val_acc: 0.8515
Epoch 4/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2075 - acc: 0.9703Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2068 - acc: 0.9704 - val_loss: 1.7726 - val_acc: 0.8479
Epoch 5/40
6588/6680 [============================>.] - ETA: 0s - loss: 0.1890 - acc: 0.9733Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1922 - acc: 0.9731 - val_loss: 1.8228 - val_acc: 0.8395
Epoch 6/40
6588/6680 [============================>.] - ETA: 0s - loss: 0.2316 - acc: 0.9686Epoch 00006: val_loss improved from 1.71629 to 1.71116, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 538us/step - loss: 0.2341 - acc: 0.9680 - val_loss: 1.7112 - val_acc: 0.8515
Epoch 7/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2016 - acc: 0.9724Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2010 - acc: 0.9725 - val_loss: 1.7687 - val_acc: 0.8563
Epoch 8/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2039 - acc: 0.9734Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2033 - acc: 0.9735 - val_loss: 1.7353 - val_acc: 0.8539
Epoch 9/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2333 - acc: 0.9715Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2368 - acc: 0.9713 - val_loss: 1.7669 - val_acc: 0.8515
Epoch 10/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2147 - acc: 0.9707Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2132 - acc: 0.9708 - val_loss: 1.7377 - val_acc: 0.8527
Epoch 11/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1958 - acc: 0.9746Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1942 - acc: 0.9749 - val_loss: 1.7925 - val_acc: 0.8455
Epoch 12/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1916 - acc: 0.9746Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1943 - acc: 0.9744 - val_loss: 1.7652 - val_acc: 0.8503
Epoch 13/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2224 - acc: 0.9758Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2215 - acc: 0.9759 - val_loss: 1.7391 - val_acc: 0.8539
Epoch 14/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2441 - acc: 0.9697Epoch 00014: val_loss improved from 1.71116 to 1.70034, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 538us/step - loss: 0.2445 - acc: 0.9698 - val_loss: 1.7003 - val_acc: 0.8587
Epoch 15/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2023 - acc: 0.9740Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2021 - acc: 0.9740 - val_loss: 1.7372 - val_acc: 0.8527
Epoch 16/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.1969 - acc: 0.9745Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1973 - acc: 0.9744 - val_loss: 1.7079 - val_acc: 0.8563
Epoch 17/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2109 - acc: 0.9712Epoch 00017: val_loss improved from 1.70034 to 1.67153, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 555us/step - loss: 0.2103 - acc: 0.9713 - val_loss: 1.6715 - val_acc: 0.8575
Epoch 18/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.1965 - acc: 0.9745Epoch 00018: val_loss improved from 1.67153 to 1.61047, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 548us/step - loss: 0.1959 - acc: 0.9746 - val_loss: 1.6105 - val_acc: 0.8647
Epoch 19/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2098 - acc: 0.9710Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2084 - acc: 0.9711 - val_loss: 1.7775 - val_acc: 0.8563
Epoch 20/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2061 - acc: 0.9737Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2044 - acc: 0.9740 - val_loss: 1.7165 - val_acc: 0.8587
Epoch 21/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2317 - acc: 0.9710Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2318 - acc: 0.9710 - val_loss: 1.6813 - val_acc: 0.8527
Epoch 22/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1893 - acc: 0.9739Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1943 - acc: 0.9735 - val_loss: 1.6457 - val_acc: 0.8611
Epoch 23/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2286 - acc: 0.9721Epoch 00023: val_loss improved from 1.61047 to 1.60085, saving model to saved_models2/weights.best.ResNet_bs36_ep40.hdf5
6680/6680 [==============================] - 4s 548us/step - loss: 0.2268 - acc: 0.9723 - val_loss: 1.6008 - val_acc: 0.8671
Epoch 24/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2088 - acc: 0.9743Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.2080 - acc: 0.9744 - val_loss: 1.7435 - val_acc: 0.8587
Epoch 25/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.1918 - acc: 0.9751Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1923 - acc: 0.9750 - val_loss: 1.7605 - val_acc: 0.8623
Epoch 26/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.1974 - acc: 0.9740Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1968 - acc: 0.9741 - val_loss: 1.8156 - val_acc: 0.8491
Epoch 27/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2090 - acc: 0.9739Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2075 - acc: 0.9740 - val_loss: 1.7038 - val_acc: 0.8551
Epoch 28/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2203 - acc: 0.9740Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2197 - acc: 0.9741 - val_loss: 1.7445 - val_acc: 0.8563
Epoch 29/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2387 - acc: 0.9710Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2386 - acc: 0.9710 - val_loss: 1.7786 - val_acc: 0.8587
Epoch 30/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1789 - acc: 0.9764Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1775 - acc: 0.9766 - val_loss: 1.8230 - val_acc: 0.8503
Epoch 31/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2164 - acc: 0.9725Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2203 - acc: 0.9723 - val_loss: 1.7785 - val_acc: 0.8551
Epoch 32/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2354 - acc: 0.9710Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2356 - acc: 0.9710 - val_loss: 1.8548 - val_acc: 0.8479
Epoch 33/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2163 - acc: 0.9743Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2177 - acc: 0.9743 - val_loss: 1.8467 - val_acc: 0.8455
Epoch 34/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1890 - acc: 0.9745Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.1876 - acc: 0.9746 - val_loss: 1.8162 - val_acc: 0.8467
Epoch 35/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.2042 - acc: 0.9760Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2036 - acc: 0.9760 - val_loss: 1.8091 - val_acc: 0.8515
Epoch 36/40
6660/6680 [============================>.] - ETA: 0s - loss: 0.1854 - acc: 0.9760Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1848 - acc: 0.9760 - val_loss: 1.7366 - val_acc: 0.8623
Epoch 37/40
6588/6680 [============================>.] - ETA: 0s - loss: 0.2249 - acc: 0.9715Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2219 - acc: 0.9719 - val_loss: 1.7641 - val_acc: 0.8611
Epoch 38/40
6588/6680 [============================>.] - ETA: 0s - loss: 0.2288 - acc: 0.9737Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2283 - acc: 0.9738 - val_loss: 1.8036 - val_acc: 0.8623
Epoch 39/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.1913 - acc: 0.9745Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1919 - acc: 0.9743 - val_loss: 1.7460 - val_acc: 0.8527
Epoch 40/40
6624/6680 [============================>.] - ETA: 0s - loss: 0.2100 - acc: 0.9731Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2086 - acc: 0.9732 - val_loss: 1.8714 - val_acc: 0.8479

Batch size=36 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2126 - acc: 0.9727Epoch 00001: val_loss improved from inf to 1.71068, saving model to saved_models2/weights.best.ResNet_bs36_ep50.hdf5
6680/6680 [==============================] - 4s 543us/step - loss: 0.2139 - acc: 0.9726 - val_loss: 1.7107 - val_acc: 0.8563
Epoch 2/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2159 - acc: 0.9725Epoch 00002: val_loss improved from 1.71068 to 1.65420, saving model to saved_models2/weights.best.ResNet_bs36_ep50.hdf5
6680/6680 [==============================] - 4s 552us/step - loss: 0.2155 - acc: 0.9725 - val_loss: 1.6542 - val_acc: 0.8623
Epoch 3/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1978 - acc: 0.9749Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 547us/step - loss: 0.1981 - acc: 0.9750 - val_loss: 1.7233 - val_acc: 0.8455
Epoch 4/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2238 - acc: 0.9721Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2232 - acc: 0.9722 - val_loss: 1.7697 - val_acc: 0.8443
Epoch 5/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2346 - acc: 0.9710Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2329 - acc: 0.9711 - val_loss: 1.7041 - val_acc: 0.8551
Epoch 6/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1976 - acc: 0.9740Epoch 00006: val_loss improved from 1.65420 to 1.64808, saving model to saved_models2/weights.best.ResNet_bs36_ep50.hdf5
6680/6680 [==============================] - 4s 541us/step - loss: 0.1972 - acc: 0.9740 - val_loss: 1.6481 - val_acc: 0.8503
Epoch 7/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2554 - acc: 0.9694Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2568 - acc: 0.9693 - val_loss: 1.6885 - val_acc: 0.8551
Epoch 8/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1821 - acc: 0.9758Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1821 - acc: 0.9757 - val_loss: 1.7016 - val_acc: 0.8539
Epoch 9/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2097 - acc: 0.9731Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.2140 - acc: 0.9726 - val_loss: 1.6538 - val_acc: 0.8575
Epoch 10/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2064 - acc: 0.9746Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2059 - acc: 0.9747 - val_loss: 1.6961 - val_acc: 0.8527
Epoch 11/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2245 - acc: 0.9733Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2259 - acc: 0.9731 - val_loss: 1.6971 - val_acc: 0.8551
Epoch 12/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2187 - acc: 0.9716Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2231 - acc: 0.9714 - val_loss: 1.7222 - val_acc: 0.8599
Epoch 13/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2124 - acc: 0.9736Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2117 - acc: 0.9737 - val_loss: 1.6610 - val_acc: 0.8539
Epoch 14/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2216 - acc: 0.9737Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2234 - acc: 0.9737 - val_loss: 1.6563 - val_acc: 0.8575
Epoch 15/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1825 - acc: 0.9789Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1846 - acc: 0.9784 - val_loss: 1.6610 - val_acc: 0.8623
Epoch 16/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1876 - acc: 0.9747Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1902 - acc: 0.9746 - val_loss: 1.6840 - val_acc: 0.8503
Epoch 17/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2058 - acc: 0.9745Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2065 - acc: 0.9746 - val_loss: 1.6973 - val_acc: 0.8563
Epoch 18/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1903 - acc: 0.9743Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1905 - acc: 0.9743 - val_loss: 1.6814 - val_acc: 0.8599
Epoch 19/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2057 - acc: 0.9733Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2051 - acc: 0.9734 - val_loss: 1.7473 - val_acc: 0.8575
Epoch 20/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1712 - acc: 0.9783Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 553us/step - loss: 0.1697 - acc: 0.9784 - val_loss: 1.6989 - val_acc: 0.8575
Epoch 21/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.2091 - acc: 0.9721Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2127 - acc: 0.9717 - val_loss: 1.7971 - val_acc: 0.8515
Epoch 22/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1998 - acc: 0.9763Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.2013 - acc: 0.9760 - val_loss: 1.8139 - val_acc: 0.8491
Epoch 23/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2182 - acc: 0.9736Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2189 - acc: 0.9735 - val_loss: 1.8076 - val_acc: 0.8551
Epoch 24/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1991 - acc: 0.9758Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1985 - acc: 0.9759 - val_loss: 1.7946 - val_acc: 0.8575
Epoch 25/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1716 - acc: 0.9787Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1750 - acc: 0.9786 - val_loss: 1.7697 - val_acc: 0.8563
Epoch 26/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2375 - acc: 0.9725Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2379 - acc: 0.9726 - val_loss: 1.7972 - val_acc: 0.8539
Epoch 27/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2090 - acc: 0.9748Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2087 - acc: 0.9747 - val_loss: 1.7589 - val_acc: 0.8599
Epoch 28/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1914 - acc: 0.9769Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 549us/step - loss: 0.1929 - acc: 0.9768 - val_loss: 1.7564 - val_acc: 0.8575
Epoch 29/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2066 - acc: 0.9745Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2071 - acc: 0.9746 - val_loss: 1.8331 - val_acc: 0.8539
Epoch 30/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2043 - acc: 0.9748Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2026 - acc: 0.9750 - val_loss: 1.8770 - val_acc: 0.8551
Epoch 31/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2036 - acc: 0.9751Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2030 - acc: 0.9751 - val_loss: 1.9126 - val_acc: 0.8491
Epoch 32/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2038 - acc: 0.9761Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2048 - acc: 0.9760 - val_loss: 1.8715 - val_acc: 0.8527
Epoch 33/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.2179 - acc: 0.9756Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2166 - acc: 0.9754 - val_loss: 1.7915 - val_acc: 0.8611
Epoch 34/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1994 - acc: 0.9763Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1978 - acc: 0.9765 - val_loss: 1.8318 - val_acc: 0.8551
Epoch 35/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2190 - acc: 0.9745Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2202 - acc: 0.9744 - val_loss: 1.8119 - val_acc: 0.8527
Epoch 36/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1751 - acc: 0.9789Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1746 - acc: 0.9789 - val_loss: 1.7348 - val_acc: 0.8503
Epoch 37/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1734 - acc: 0.9795Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1741 - acc: 0.9792 - val_loss: 1.8429 - val_acc: 0.8503
Epoch 38/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1709 - acc: 0.9802Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1715 - acc: 0.9799 - val_loss: 1.7520 - val_acc: 0.8587
Epoch 39/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1778 - acc: 0.9778Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1773 - acc: 0.9778 - val_loss: 1.7298 - val_acc: 0.8575
Epoch 40/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2034 - acc: 0.9746Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2028 - acc: 0.9747 - val_loss: 1.7199 - val_acc: 0.8551
Epoch 41/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2127 - acc: 0.9755Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2141 - acc: 0.9753 - val_loss: 1.7542 - val_acc: 0.8551
Epoch 42/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1913 - acc: 0.9745Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1897 - acc: 0.9747 - val_loss: 1.7214 - val_acc: 0.8563
Epoch 43/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2035 - acc: 0.9767Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2029 - acc: 0.9768 - val_loss: 1.8409 - val_acc: 0.8527
Epoch 44/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1722 - acc: 0.9803Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1728 - acc: 0.9799 - val_loss: 1.9316 - val_acc: 0.8515
Epoch 45/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.2135 - acc: 0.9746Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2129 - acc: 0.9747 - val_loss: 1.7724 - val_acc: 0.8527
Epoch 46/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.2072 - acc: 0.9754Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.2054 - acc: 0.9756 - val_loss: 1.7570 - val_acc: 0.8575
Epoch 47/50
6660/6680 [============================>.] - ETA: 0s - loss: 0.1560 - acc: 0.9821Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1578 - acc: 0.9819 - val_loss: 1.7658 - val_acc: 0.8575
Epoch 48/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1891 - acc: 0.9766Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1940 - acc: 0.9762 - val_loss: 1.8177 - val_acc: 0.8599
Epoch 49/50
6588/6680 [============================>.] - ETA: 0s - loss: 0.1753 - acc: 0.9783Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1751 - acc: 0.9783 - val_loss: 1.8535 - val_acc: 0.8515
Epoch 50/50
6624/6680 [============================>.] - ETA: 0s - loss: 0.1928 - acc: 0.9772Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1936 - acc: 0.9772 - val_loss: 1.7073 - val_acc: 0.8611

Batch size=36 Epoch=55
Train on 6680 samples, validate on 835 samples
Epoch 1/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2135 - acc: 0.9752Epoch 00001: val_loss improved from inf to 1.67392, saving model to saved_models2/weights.best.ResNet_bs36_ep55.hdf5
6680/6680 [==============================] - 4s 542us/step - loss: 0.2117 - acc: 0.9754 - val_loss: 1.6739 - val_acc: 0.8479
Epoch 2/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2073 - acc: 0.9728Epoch 00002: val_loss improved from 1.67392 to 1.64500, saving model to saved_models2/weights.best.ResNet_bs36_ep55.hdf5
6680/6680 [==============================] - 4s 531us/step - loss: 0.2079 - acc: 0.9728 - val_loss: 1.6450 - val_acc: 0.8599
Epoch 3/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.2006 - acc: 0.9737Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1986 - acc: 0.9737 - val_loss: 1.7052 - val_acc: 0.8491
Epoch 4/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2330 - acc: 0.9716Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2323 - acc: 0.9717 - val_loss: 1.7535 - val_acc: 0.8479
Epoch 5/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2159 - acc: 0.9737Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2141 - acc: 0.9740 - val_loss: 1.6464 - val_acc: 0.8647
Epoch 6/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1974 - acc: 0.9766Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.1982 - acc: 0.9766 - val_loss: 1.7226 - val_acc: 0.8599
Epoch 7/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2147 - acc: 0.9736Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 545us/step - loss: 0.2185 - acc: 0.9732 - val_loss: 1.6494 - val_acc: 0.8611
Epoch 8/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1736 - acc: 0.9775Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1739 - acc: 0.9774 - val_loss: 1.7370 - val_acc: 0.8515
Epoch 9/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2062 - acc: 0.9739Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2048 - acc: 0.9740 - val_loss: 1.7680 - val_acc: 0.8563
Epoch 10/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1852 - acc: 0.9745Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1836 - acc: 0.9747 - val_loss: 1.7212 - val_acc: 0.8587
Epoch 11/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2253 - acc: 0.9748Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2258 - acc: 0.9747 - val_loss: 1.7188 - val_acc: 0.8611
Epoch 12/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1716 - acc: 0.9780Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1717 - acc: 0.9778 - val_loss: 1.8003 - val_acc: 0.8599
Epoch 13/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2205 - acc: 0.9736Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2198 - acc: 0.9737 - val_loss: 1.8085 - val_acc: 0.8575
Epoch 14/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1919 - acc: 0.9742Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1893 - acc: 0.9746 - val_loss: 1.7948 - val_acc: 0.8563
Epoch 15/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2101 - acc: 0.9734Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2095 - acc: 0.9735 - val_loss: 1.7988 - val_acc: 0.8527
Epoch 16/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2349 - acc: 0.9722Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.2342 - acc: 0.9723 - val_loss: 1.7683 - val_acc: 0.8551
Epoch 17/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1990 - acc: 0.9753Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1987 - acc: 0.9754 - val_loss: 1.7568 - val_acc: 0.8515
Epoch 18/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1829 - acc: 0.9770Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1824 - acc: 0.9771 - val_loss: 1.7447 - val_acc: 0.8527
Epoch 19/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2366 - acc: 0.9737Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2346 - acc: 0.9740 - val_loss: 1.7358 - val_acc: 0.8563
Epoch 20/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1885 - acc: 0.9774Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1881 - acc: 0.9774 - val_loss: 1.7690 - val_acc: 0.8527
Epoch 21/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2053 - acc: 0.9751Epoch 00021: val_loss improved from 1.64500 to 1.63541, saving model to saved_models2/weights.best.ResNet_bs36_ep55.hdf5
6680/6680 [==============================] - 4s 542us/step - loss: 0.2043 - acc: 0.9751 - val_loss: 1.6354 - val_acc: 0.8647
Epoch 22/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1734 - acc: 0.9790Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1728 - acc: 0.9790 - val_loss: 1.7122 - val_acc: 0.8587
Epoch 23/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1806 - acc: 0.9781Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1800 - acc: 0.9781 - val_loss: 1.7285 - val_acc: 0.8527
Epoch 24/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2007 - acc: 0.9746Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2009 - acc: 0.9746 - val_loss: 1.7216 - val_acc: 0.8587
Epoch 25/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2210 - acc: 0.9734Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.2200 - acc: 0.9735 - val_loss: 1.7650 - val_acc: 0.8551
Epoch 26/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2249 - acc: 0.9752Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2237 - acc: 0.9753 - val_loss: 1.7636 - val_acc: 0.8467
Epoch 27/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1789 - acc: 0.9766Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1806 - acc: 0.9763 - val_loss: 1.7544 - val_acc: 0.8539
Epoch 28/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1952 - acc: 0.9751Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1936 - acc: 0.9753 - val_loss: 1.8146 - val_acc: 0.8539
Epoch 29/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1982 - acc: 0.9748Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2000 - acc: 0.9747 - val_loss: 1.8471 - val_acc: 0.8515
Epoch 30/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2085 - acc: 0.9751Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.2079 - acc: 0.9751 - val_loss: 1.8337 - val_acc: 0.8551
Epoch 31/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2264 - acc: 0.9733Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.2258 - acc: 0.9734 - val_loss: 1.8259 - val_acc: 0.8527
Epoch 32/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2042 - acc: 0.9774Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2025 - acc: 0.9775 - val_loss: 1.8255 - val_acc: 0.8479
Epoch 33/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1916 - acc: 0.9774Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1932 - acc: 0.9772 - val_loss: 1.8402 - val_acc: 0.8515
Epoch 34/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1775 - acc: 0.9780Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1810 - acc: 0.9778 - val_loss: 1.8115 - val_acc: 0.8503
Epoch 35/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2073 - acc: 0.9749Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2068 - acc: 0.9750 - val_loss: 1.8045 - val_acc: 0.8455
Epoch 36/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.2039 - acc: 0.9779Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2033 - acc: 0.9780 - val_loss: 1.8855 - val_acc: 0.8491
Epoch 37/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1867 - acc: 0.9766Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1864 - acc: 0.9765 - val_loss: 1.8303 - val_acc: 0.8491
Epoch 38/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2035 - acc: 0.9763Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2072 - acc: 0.9760 - val_loss: 1.8129 - val_acc: 0.8479
Epoch 39/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2119 - acc: 0.9760Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2143 - acc: 0.9757 - val_loss: 1.8393 - val_acc: 0.8539
Epoch 40/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2120 - acc: 0.9748Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2130 - acc: 0.9746 - val_loss: 1.8798 - val_acc: 0.8467
Epoch 41/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1995 - acc: 0.9766Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1989 - acc: 0.9766 - val_loss: 1.7576 - val_acc: 0.8515
Epoch 42/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2089 - acc: 0.9780Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.2072 - acc: 0.9781 - val_loss: 1.8129 - val_acc: 0.8503
Epoch 43/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1933 - acc: 0.9786Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1961 - acc: 0.9784 - val_loss: 1.7830 - val_acc: 0.8587
Epoch 44/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1946 - acc: 0.9778Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1978 - acc: 0.9772 - val_loss: 1.7904 - val_acc: 0.8623
Epoch 45/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.2206 - acc: 0.9743Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.2180 - acc: 0.9746 - val_loss: 1.7979 - val_acc: 0.8551
Epoch 46/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1649 - acc: 0.9797Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 544us/step - loss: 0.1644 - acc: 0.9798 - val_loss: 1.8667 - val_acc: 0.8503
Epoch 47/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1632 - acc: 0.9796Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1627 - acc: 0.9796 - val_loss: 1.8407 - val_acc: 0.8479
Epoch 48/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2429 - acc: 0.9727Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2439 - acc: 0.9725 - val_loss: 1.8288 - val_acc: 0.8563
Epoch 49/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1909 - acc: 0.9778Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1903 - acc: 0.9778 - val_loss: 1.8913 - val_acc: 0.8563
Epoch 50/55
6588/6680 [============================>.] - ETA: 0s - loss: 0.1906 - acc: 0.9771Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1931 - acc: 0.9769 - val_loss: 1.8775 - val_acc: 0.8455
Epoch 51/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1922 - acc: 0.9793Epoch 00051: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1914 - acc: 0.9793 - val_loss: 1.8322 - val_acc: 0.8539
Epoch 52/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1898 - acc: 0.9755Epoch 00052: val_loss did not improve
6680/6680 [==============================] - 4s 541us/step - loss: 0.1916 - acc: 0.9754 - val_loss: 1.8367 - val_acc: 0.8551
Epoch 53/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1772 - acc: 0.9802Epoch 00053: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1759 - acc: 0.9802 - val_loss: 1.8580 - val_acc: 0.8527
Epoch 54/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.1846 - acc: 0.9778Epoch 00054: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1831 - acc: 0.9780 - val_loss: 1.7985 - val_acc: 0.8623
Epoch 55/55
6624/6680 [============================>.] - ETA: 0s - loss: 0.2000 - acc: 0.9758Epoch 00055: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1991 - acc: 0.9759 - val_loss: 1.8406 - val_acc: 0.8551

Batch size=37 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2130 - acc: 0.9751Epoch 00001: val_loss improved from inf to 1.70352, saving model to saved_models2/weights.best.ResNet_bs37_ep35.hdf5
6680/6680 [==============================] - 4s 539us/step - loss: 0.2125 - acc: 0.9751 - val_loss: 1.7035 - val_acc: 0.8575
Epoch 2/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1865 - acc: 0.9756Epoch 00002: val_loss improved from 1.70352 to 1.66106, saving model to saved_models2/weights.best.ResNet_bs37_ep35.hdf5
6680/6680 [==============================] - 4s 535us/step - loss: 0.1848 - acc: 0.9757 - val_loss: 1.6611 - val_acc: 0.8539
Epoch 3/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2134 - acc: 0.9756Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2112 - acc: 0.9756 - val_loss: 1.8065 - val_acc: 0.8611
Epoch 4/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2337 - acc: 0.9713Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2347 - acc: 0.9713 - val_loss: 1.7334 - val_acc: 0.8587
Epoch 5/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2139 - acc: 0.9746Epoch 00005: val_loss improved from 1.66106 to 1.65937, saving model to saved_models2/weights.best.ResNet_bs37_ep35.hdf5
6680/6680 [==============================] - 4s 536us/step - loss: 0.2117 - acc: 0.9749 - val_loss: 1.6594 - val_acc: 0.8623
Epoch 6/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2215 - acc: 0.9759Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2210 - acc: 0.9759 - val_loss: 1.6858 - val_acc: 0.8623
Epoch 7/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1714 - acc: 0.9784Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1690 - acc: 0.9787 - val_loss: 1.7468 - val_acc: 0.8587
Epoch 8/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1804 - acc: 0.9786Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1841 - acc: 0.9783 - val_loss: 1.7452 - val_acc: 0.8623
Epoch 9/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1627 - acc: 0.9790Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1604 - acc: 0.9793 - val_loss: 1.7622 - val_acc: 0.8611
Epoch 10/35
6623/6680 [============================>.] - ETA: 0s - loss: 0.1939 - acc: 0.9761Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1953 - acc: 0.9760 - val_loss: 1.7538 - val_acc: 0.8599
Epoch 11/35
6623/6680 [============================>.] - ETA: 0s - loss: 0.1736 - acc: 0.9787Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1727 - acc: 0.9787 - val_loss: 1.7812 - val_acc: 0.8551
Epoch 12/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1983 - acc: 0.9780Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1990 - acc: 0.9778 - val_loss: 1.8289 - val_acc: 0.8515
Epoch 13/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2105 - acc: 0.9743Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2082 - acc: 0.9746 - val_loss: 1.8180 - val_acc: 0.8563
Epoch 14/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2003 - acc: 0.9757Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1981 - acc: 0.9759 - val_loss: 1.7166 - val_acc: 0.8611
Epoch 15/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1776 - acc: 0.9775Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1797 - acc: 0.9772 - val_loss: 1.8218 - val_acc: 0.8599
Epoch 16/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2206 - acc: 0.9737Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.2194 - acc: 0.9740 - val_loss: 1.7906 - val_acc: 0.8539
Epoch 17/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1827 - acc: 0.9778Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1820 - acc: 0.9778 - val_loss: 1.7174 - val_acc: 0.8647
Epoch 18/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1657 - acc: 0.9787Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 524us/step - loss: 0.1679 - acc: 0.9787 - val_loss: 1.8582 - val_acc: 0.8551
Epoch 19/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1816 - acc: 0.9784Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1813 - acc: 0.9784 - val_loss: 1.8112 - val_acc: 0.8491
Epoch 20/35
6623/6680 [============================>.] - ETA: 0s - loss: 0.1844 - acc: 0.9760Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1829 - acc: 0.9762 - val_loss: 1.8937 - val_acc: 0.8515
Epoch 21/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1965 - acc: 0.9772Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1977 - acc: 0.9771 - val_loss: 1.8383 - val_acc: 0.8491
Epoch 22/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2023 - acc: 0.9753Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2022 - acc: 0.9753 - val_loss: 1.7561 - val_acc: 0.8563
Epoch 23/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1705 - acc: 0.9786Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1698 - acc: 0.9787 - val_loss: 1.7440 - val_acc: 0.8611
Epoch 24/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1881 - acc: 0.9784Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1911 - acc: 0.9783 - val_loss: 1.7081 - val_acc: 0.8563
Epoch 25/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1845 - acc: 0.9781Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1864 - acc: 0.9780 - val_loss: 1.8112 - val_acc: 0.8539
Epoch 26/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1894 - acc: 0.9762Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1882 - acc: 0.9760 - val_loss: 1.7800 - val_acc: 0.8551
Epoch 27/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2103 - acc: 0.9763Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.2099 - acc: 0.9763 - val_loss: 1.8006 - val_acc: 0.8599
Epoch 28/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1875 - acc: 0.9783Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 546us/step - loss: 0.1908 - acc: 0.9781 - val_loss: 1.7468 - val_acc: 0.8563
Epoch 29/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1997 - acc: 0.9778Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2036 - acc: 0.9777 - val_loss: 1.7157 - val_acc: 0.8599
Epoch 30/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.2162 - acc: 0.9748Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2144 - acc: 0.9749 - val_loss: 1.8250 - val_acc: 0.8551
Epoch 31/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1434 - acc: 0.9810Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1415 - acc: 0.9813 - val_loss: 1.8280 - val_acc: 0.8539
Epoch 32/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1942 - acc: 0.9774Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1922 - acc: 0.9774 - val_loss: 1.8280 - val_acc: 0.8539
Epoch 33/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1857 - acc: 0.9780Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1843 - acc: 0.9781 - val_loss: 1.8910 - val_acc: 0.8527
Epoch 34/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1763 - acc: 0.9801Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1749 - acc: 0.9802 - val_loss: 1.8058 - val_acc: 0.8611
Epoch 35/35
6586/6680 [============================>.] - ETA: 0s - loss: 0.1710 - acc: 0.9790Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1697 - acc: 0.9790 - val_loss: 1.8984 - val_acc: 0.8455

Batch size=37 Epoch=37
Train on 6680 samples, validate on 835 samples
Epoch 1/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1777 - acc: 0.9769Epoch 00001: val_loss improved from inf to 1.68524, saving model to saved_models2/weights.best.ResNet_bs37_ep37.hdf5
6680/6680 [==============================] - 4s 539us/step - loss: 0.1755 - acc: 0.9771 - val_loss: 1.6852 - val_acc: 0.8623
Epoch 2/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1986 - acc: 0.9756Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1984 - acc: 0.9756 - val_loss: 1.7902 - val_acc: 0.8575
Epoch 3/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1893 - acc: 0.9780Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1876 - acc: 0.9781 - val_loss: 1.7333 - val_acc: 0.8647
Epoch 4/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1749 - acc: 0.9809Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1744 - acc: 0.9804 - val_loss: 1.6864 - val_acc: 0.8575
Epoch 5/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1842 - acc: 0.9771Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1860 - acc: 0.9769 - val_loss: 1.7823 - val_acc: 0.8539
Epoch 6/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2208 - acc: 0.9727Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2261 - acc: 0.9723 - val_loss: 1.7973 - val_acc: 0.8587
Epoch 7/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1807 - acc: 0.9784Epoch 00007: val_loss improved from 1.68524 to 1.66562, saving model to saved_models2/weights.best.ResNet_bs37_ep37.hdf5
6680/6680 [==============================] - 4s 536us/step - loss: 0.1835 - acc: 0.9783 - val_loss: 1.6656 - val_acc: 0.8611
Epoch 8/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2002 - acc: 0.9765Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1983 - acc: 0.9766 - val_loss: 1.6746 - val_acc: 0.8611
Epoch 9/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1827 - acc: 0.9784Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1810 - acc: 0.9784 - val_loss: 1.7670 - val_acc: 0.8563
Epoch 10/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2095 - acc: 0.9746Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 524us/step - loss: 0.2080 - acc: 0.9749 - val_loss: 1.8001 - val_acc: 0.8551
Epoch 11/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1960 - acc: 0.9777Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1961 - acc: 0.9775 - val_loss: 1.8447 - val_acc: 0.8551
Epoch 12/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1903 - acc: 0.9772Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1877 - acc: 0.9775 - val_loss: 1.7268 - val_acc: 0.8671
Epoch 13/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1688 - acc: 0.9792Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1681 - acc: 0.9793 - val_loss: 1.7294 - val_acc: 0.8623
Epoch 14/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1943 - acc: 0.9766Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1916 - acc: 0.9769 - val_loss: 1.7526 - val_acc: 0.8623
Epoch 15/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1733 - acc: 0.9790Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1709 - acc: 0.9793 - val_loss: 1.7672 - val_acc: 0.8551
Epoch 16/37
6623/6680 [============================>.] - ETA: 0s - loss: 0.1679 - acc: 0.9804Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1694 - acc: 0.9802 - val_loss: 1.7865 - val_acc: 0.8563
Epoch 17/37
6623/6680 [============================>.] - ETA: 0s - loss: 0.1861 - acc: 0.9799Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1845 - acc: 0.9801 - val_loss: 1.6916 - val_acc: 0.8623
Epoch 18/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1638 - acc: 0.9803Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1690 - acc: 0.9799 - val_loss: 1.7159 - val_acc: 0.8623
Epoch 19/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1865 - acc: 0.9766Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1873 - acc: 0.9765 - val_loss: 1.7846 - val_acc: 0.8599
Epoch 20/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1781 - acc: 0.9775Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1773 - acc: 0.9777 - val_loss: 1.8404 - val_acc: 0.8539
Epoch 21/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1692 - acc: 0.9789Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1685 - acc: 0.9790 - val_loss: 1.8126 - val_acc: 0.8587
Epoch 22/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2104 - acc: 0.9757Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.2108 - acc: 0.9756 - val_loss: 1.8845 - val_acc: 0.8563
Epoch 23/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1774 - acc: 0.9780Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1773 - acc: 0.9781 - val_loss: 1.8281 - val_acc: 0.8527
Epoch 24/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1810 - acc: 0.9786Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1839 - acc: 0.9783 - val_loss: 1.8551 - val_acc: 0.8551
Epoch 25/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1554 - acc: 0.9821Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1571 - acc: 0.9819 - val_loss: 1.8344 - val_acc: 0.8515
Epoch 26/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2021 - acc: 0.9756Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.2010 - acc: 0.9756 - val_loss: 1.7498 - val_acc: 0.8623
Epoch 27/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1883 - acc: 0.9787Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 524us/step - loss: 0.1905 - acc: 0.9787 - val_loss: 1.7987 - val_acc: 0.8575
Epoch 28/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1737 - acc: 0.9795Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1716 - acc: 0.9796 - val_loss: 1.7956 - val_acc: 0.8575
Epoch 29/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1563 - acc: 0.9806Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1555 - acc: 0.9805 - val_loss: 1.7825 - val_acc: 0.8551
Epoch 30/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1505 - acc: 0.9821Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1512 - acc: 0.9819 - val_loss: 1.8277 - val_acc: 0.8623
Epoch 31/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1634 - acc: 0.9822Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1636 - acc: 0.9823 - val_loss: 1.9087 - val_acc: 0.8491
Epoch 32/37
6623/6680 [============================>.] - ETA: 0s - loss: 0.1976 - acc: 0.9770Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1982 - acc: 0.9769 - val_loss: 1.7628 - val_acc: 0.8647
Epoch 33/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1692 - acc: 0.9815Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1668 - acc: 0.9817 - val_loss: 1.7996 - val_acc: 0.8563
Epoch 34/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1612 - acc: 0.9822Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1602 - acc: 0.9820 - val_loss: 1.8442 - val_acc: 0.8515
Epoch 35/37
6623/6680 [============================>.] - ETA: 0s - loss: 0.1769 - acc: 0.9802Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 518us/step - loss: 0.1754 - acc: 0.9804 - val_loss: 1.8948 - val_acc: 0.8467
Epoch 36/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.2006 - acc: 0.9775Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1979 - acc: 0.9778 - val_loss: 1.8400 - val_acc: 0.8563
Epoch 37/37
6586/6680 [============================>.] - ETA: 0s - loss: 0.1799 - acc: 0.9800Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1799 - acc: 0.9799 - val_loss: 1.8637 - val_acc: 0.8587

Batch size=37 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1981 - acc: 0.9774Epoch 00001: val_loss improved from inf to 1.75257, saving model to saved_models2/weights.best.ResNet_bs37_ep40.hdf5
6680/6680 [==============================] - 4s 542us/step - loss: 0.1958 - acc: 0.9775 - val_loss: 1.7526 - val_acc: 0.8575
Epoch 2/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1781 - acc: 0.9774Epoch 00002: val_loss improved from 1.75257 to 1.66336, saving model to saved_models2/weights.best.ResNet_bs37_ep40.hdf5
6680/6680 [==============================] - 4s 535us/step - loss: 0.1756 - acc: 0.9777 - val_loss: 1.6634 - val_acc: 0.8647
Epoch 3/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1990 - acc: 0.9769Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.2010 - acc: 0.9768 - val_loss: 1.6720 - val_acc: 0.8635
Epoch 4/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1800 - acc: 0.9784Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1799 - acc: 0.9786 - val_loss: 1.7363 - val_acc: 0.8647
Epoch 5/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2098 - acc: 0.9763Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2092 - acc: 0.9763 - val_loss: 1.7968 - val_acc: 0.8515
Epoch 6/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1844 - acc: 0.9768Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1830 - acc: 0.9769 - val_loss: 1.7606 - val_acc: 0.8635
Epoch 7/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1528 - acc: 0.9816Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1542 - acc: 0.9816 - val_loss: 1.8908 - val_acc: 0.8575
Epoch 8/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2273 - acc: 0.9754Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.2292 - acc: 0.9753 - val_loss: 1.8824 - val_acc: 0.8587
Epoch 9/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1770 - acc: 0.9783Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1746 - acc: 0.9786 - val_loss: 1.7654 - val_acc: 0.8515
Epoch 10/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2009 - acc: 0.9751Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2002 - acc: 0.9753 - val_loss: 1.8786 - val_acc: 0.8575
Epoch 11/40
6623/6680 [============================>.] - ETA: 0s - loss: 0.1737 - acc: 0.9786Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1801 - acc: 0.9778 - val_loss: 1.8096 - val_acc: 0.8551
Epoch 12/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1776 - acc: 0.9790Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1794 - acc: 0.9789 - val_loss: 1.8066 - val_acc: 0.8599
Epoch 13/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1695 - acc: 0.9780Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1705 - acc: 0.9777 - val_loss: 1.8488 - val_acc: 0.8611
Epoch 14/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1881 - acc: 0.9783Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 520us/step - loss: 0.1876 - acc: 0.9783 - val_loss: 1.8635 - val_acc: 0.8551
Epoch 15/40
6623/6680 [============================>.] - ETA: 0s - loss: 0.2063 - acc: 0.9778Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 521us/step - loss: 0.2056 - acc: 0.9778 - val_loss: 1.8145 - val_acc: 0.8539
Epoch 16/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1852 - acc: 0.9787Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1844 - acc: 0.9789 - val_loss: 1.8339 - val_acc: 0.8539
Epoch 17/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1905 - acc: 0.9760Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1878 - acc: 0.9763 - val_loss: 1.8363 - val_acc: 0.8479
Epoch 18/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1935 - acc: 0.9766Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1918 - acc: 0.9766 - val_loss: 1.8393 - val_acc: 0.8563
Epoch 19/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1856 - acc: 0.9781Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1861 - acc: 0.9781 - val_loss: 1.8784 - val_acc: 0.8491
Epoch 20/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1755 - acc: 0.9800Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1737 - acc: 0.9801 - val_loss: 1.8783 - val_acc: 0.8527
Epoch 21/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1756 - acc: 0.9798Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 521us/step - loss: 0.1755 - acc: 0.9799 - val_loss: 1.8916 - val_acc: 0.8491
Epoch 22/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1855 - acc: 0.9786Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 524us/step - loss: 0.1844 - acc: 0.9786 - val_loss: 2.0117 - val_acc: 0.8443
Epoch 23/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1859 - acc: 0.9801Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1881 - acc: 0.9799 - val_loss: 1.9864 - val_acc: 0.8479
Epoch 24/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1815 - acc: 0.9787Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1835 - acc: 0.9787 - val_loss: 1.9041 - val_acc: 0.8443
Epoch 25/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1976 - acc: 0.9777Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1957 - acc: 0.9777 - val_loss: 1.8921 - val_acc: 0.8515
Epoch 26/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2192 - acc: 0.9756Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2168 - acc: 0.9757 - val_loss: 1.8800 - val_acc: 0.8599
Epoch 27/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1785 - acc: 0.9778Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1796 - acc: 0.9777 - val_loss: 1.8814 - val_acc: 0.8527
Epoch 28/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1583 - acc: 0.9821Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1561 - acc: 0.9823 - val_loss: 1.8202 - val_acc: 0.8575
Epoch 29/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2063 - acc: 0.9771Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2034 - acc: 0.9774 - val_loss: 1.9393 - val_acc: 0.8479
Epoch 30/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1574 - acc: 0.9807Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1609 - acc: 0.9805 - val_loss: 1.9000 - val_acc: 0.8491
Epoch 31/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2134 - acc: 0.9763Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.2160 - acc: 0.9757 - val_loss: 1.9178 - val_acc: 0.8491
Epoch 32/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1707 - acc: 0.9804Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1699 - acc: 0.9802 - val_loss: 1.8310 - val_acc: 0.8587
Epoch 33/40
6623/6680 [============================>.] - ETA: 0s - loss: 0.1745 - acc: 0.9802Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1736 - acc: 0.9802 - val_loss: 1.9120 - val_acc: 0.8539
Epoch 34/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1601 - acc: 0.9824Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1594 - acc: 0.9823 - val_loss: 1.8268 - val_acc: 0.8527
Epoch 35/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.2096 - acc: 0.9769Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.2086 - acc: 0.9771 - val_loss: 1.7704 - val_acc: 0.8539
Epoch 36/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1699 - acc: 0.9797Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1683 - acc: 0.9798 - val_loss: 1.8887 - val_acc: 0.8515
Epoch 37/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1637 - acc: 0.9803Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 543us/step - loss: 0.1680 - acc: 0.9799 - val_loss: 1.8853 - val_acc: 0.8515
Epoch 38/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1910 - acc: 0.9786Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1931 - acc: 0.9783 - val_loss: 1.8438 - val_acc: 0.8467
Epoch 39/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1674 - acc: 0.9813Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1676 - acc: 0.9813 - val_loss: 1.8933 - val_acc: 0.8383
Epoch 40/40
6586/6680 [============================>.] - ETA: 0s - loss: 0.1886 - acc: 0.9790Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1929 - acc: 0.9787 - val_loss: 1.8735 - val_acc: 0.8407

Batch size=37 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1980 - acc: 0.9757Epoch 00001: val_loss improved from inf to 1.59582, saving model to saved_models2/weights.best.ResNet_bs37_ep50.hdf5
6680/6680 [==============================] - 4s 531us/step - loss: 0.1952 - acc: 0.9760 - val_loss: 1.5958 - val_acc: 0.8707
Epoch 2/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1780 - acc: 0.9772Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1771 - acc: 0.9772 - val_loss: 1.6889 - val_acc: 0.8599
Epoch 3/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1879 - acc: 0.9772Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1870 - acc: 0.9774 - val_loss: 1.7193 - val_acc: 0.8467
Epoch 4/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2121 - acc: 0.9751Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2104 - acc: 0.9750 - val_loss: 1.8032 - val_acc: 0.8503
Epoch 5/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1867 - acc: 0.9803Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1876 - acc: 0.9802 - val_loss: 1.8706 - val_acc: 0.8443
Epoch 6/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1768 - acc: 0.9786Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1765 - acc: 0.9786 - val_loss: 1.8190 - val_acc: 0.8491
Epoch 7/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2137 - acc: 0.9757Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2154 - acc: 0.9754 - val_loss: 1.8598 - val_acc: 0.8467
Epoch 8/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2105 - acc: 0.9756Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2094 - acc: 0.9757 - val_loss: 1.8423 - val_acc: 0.8539
Epoch 9/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2016 - acc: 0.9775Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1995 - acc: 0.9777 - val_loss: 1.7886 - val_acc: 0.8527
Epoch 10/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1819 - acc: 0.9777Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 537us/step - loss: 0.1848 - acc: 0.9774 - val_loss: 1.8631 - val_acc: 0.8479
Epoch 11/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1585 - acc: 0.9798Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1602 - acc: 0.9796 - val_loss: 1.9001 - val_acc: 0.8515
Epoch 12/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1716 - acc: 0.9795Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1723 - acc: 0.9793 - val_loss: 1.9215 - val_acc: 0.8491
Epoch 13/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1914 - acc: 0.9763Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1920 - acc: 0.9763 - val_loss: 1.8247 - val_acc: 0.8551
Epoch 14/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1762 - acc: 0.9787Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1811 - acc: 0.9784 - val_loss: 1.8624 - val_acc: 0.8467
Epoch 15/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2015 - acc: 0.9766Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2017 - acc: 0.9765 - val_loss: 1.8567 - val_acc: 0.8515
Epoch 16/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1923 - acc: 0.9783Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1963 - acc: 0.9780 - val_loss: 1.9254 - val_acc: 0.8467
Epoch 17/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1400 - acc: 0.9813Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1451 - acc: 0.9808 - val_loss: 1.8947 - val_acc: 0.8467
Epoch 18/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1932 - acc: 0.9777Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1907 - acc: 0.9778 - val_loss: 1.7984 - val_acc: 0.8551
Epoch 19/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1864 - acc: 0.9797Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1898 - acc: 0.9792 - val_loss: 1.8073 - val_acc: 0.8539
Epoch 20/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1877 - acc: 0.9781Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1862 - acc: 0.9780 - val_loss: 1.8544 - val_acc: 0.8551
Epoch 21/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1724 - acc: 0.9800Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1715 - acc: 0.9799 - val_loss: 1.8036 - val_acc: 0.8503
Epoch 22/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1694 - acc: 0.9783Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1697 - acc: 0.9783 - val_loss: 1.7974 - val_acc: 0.8587
Epoch 23/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1892 - acc: 0.9790Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 524us/step - loss: 0.1886 - acc: 0.9792 - val_loss: 1.8484 - val_acc: 0.8551
Epoch 24/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2272 - acc: 0.9757Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 520us/step - loss: 0.2295 - acc: 0.9756 - val_loss: 1.7813 - val_acc: 0.8539
Epoch 25/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1793 - acc: 0.9783Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1782 - acc: 0.9784 - val_loss: 1.7815 - val_acc: 0.8527
Epoch 26/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9772Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1851 - acc: 0.9771 - val_loss: 1.8443 - val_acc: 0.8563
Epoch 27/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1758 - acc: 0.9804Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1780 - acc: 0.9801 - val_loss: 1.8617 - val_acc: 0.8491
Epoch 28/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1728 - acc: 0.9803Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1755 - acc: 0.9801 - val_loss: 1.9455 - val_acc: 0.8467
Epoch 29/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1916 - acc: 0.9777Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 4s 542us/step - loss: 0.1936 - acc: 0.9775 - val_loss: 1.9750 - val_acc: 0.8431
Epoch 30/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2130 - acc: 0.9763Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2107 - acc: 0.9763 - val_loss: 1.8778 - val_acc: 0.8551
Epoch 31/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1862 - acc: 0.9786Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1847 - acc: 0.9786 - val_loss: 1.8579 - val_acc: 0.8527
Epoch 32/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1706 - acc: 0.9797Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1730 - acc: 0.9795 - val_loss: 1.8197 - val_acc: 0.8575
Epoch 33/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1976 - acc: 0.9781Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1960 - acc: 0.9783 - val_loss: 1.8251 - val_acc: 0.8515
Epoch 34/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1569 - acc: 0.9813Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1601 - acc: 0.9811 - val_loss: 1.8400 - val_acc: 0.8563
Epoch 35/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2005 - acc: 0.9781Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.2014 - acc: 0.9781 - val_loss: 1.8667 - val_acc: 0.8515
Epoch 36/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1713 - acc: 0.9809Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1721 - acc: 0.9805 - val_loss: 1.8349 - val_acc: 0.8587
Epoch 37/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1685 - acc: 0.9798Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1671 - acc: 0.9798 - val_loss: 1.7944 - val_acc: 0.8551
Epoch 38/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1839 - acc: 0.9798Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1814 - acc: 0.9801 - val_loss: 1.8097 - val_acc: 0.8575
Epoch 39/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.2037 - acc: 0.9792Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2023 - acc: 0.9793 - val_loss: 1.8409 - val_acc: 0.8515
Epoch 40/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1603 - acc: 0.9822Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1600 - acc: 0.9822 - val_loss: 1.7496 - val_acc: 0.8575
Epoch 41/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1689 - acc: 0.9807Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1677 - acc: 0.9808 - val_loss: 1.7896 - val_acc: 0.8539
Epoch 42/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1821 - acc: 0.9790Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1831 - acc: 0.9790 - val_loss: 1.8020 - val_acc: 0.8563
Epoch 43/50
6623/6680 [============================>.] - ETA: 0s - loss: 0.1937 - acc: 0.9801Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1921 - acc: 0.9802 - val_loss: 1.7963 - val_acc: 0.8551
Epoch 44/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1810 - acc: 0.9807Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1802 - acc: 0.9808 - val_loss: 1.8630 - val_acc: 0.8527
Epoch 45/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1998 - acc: 0.9792Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1994 - acc: 0.9789 - val_loss: 1.8377 - val_acc: 0.8503
Epoch 46/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1536 - acc: 0.9813Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1596 - acc: 0.9805 - val_loss: 1.8614 - val_acc: 0.8551
Epoch 47/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1948 - acc: 0.9778Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1943 - acc: 0.9777 - val_loss: 1.8870 - val_acc: 0.8491
Epoch 48/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1837 - acc: 0.9787Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 524us/step - loss: 0.1819 - acc: 0.9787 - val_loss: 1.8924 - val_acc: 0.8515
Epoch 49/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1787 - acc: 0.9790Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1771 - acc: 0.9792 - val_loss: 1.9154 - val_acc: 0.8515
Epoch 50/50
6586/6680 [============================>.] - ETA: 0s - loss: 0.1846 - acc: 0.9772Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1820 - acc: 0.9775 - val_loss: 1.8670 - val_acc: 0.8515

Batch size=37 Epoch=55
Train on 6680 samples, validate on 835 samples
Epoch 1/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1887 - acc: 0.9794Epoch 00001: val_loss improved from inf to 1.70679, saving model to saved_models2/weights.best.ResNet_bs37_ep55.hdf5
6680/6680 [==============================] - 4s 533us/step - loss: 0.1929 - acc: 0.9786 - val_loss: 1.7068 - val_acc: 0.8563
Epoch 2/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1593 - acc: 0.9798Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1600 - acc: 0.9798 - val_loss: 1.7343 - val_acc: 0.8539
Epoch 3/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1624 - acc: 0.9801Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1649 - acc: 0.9801 - val_loss: 1.7073 - val_acc: 0.8611
Epoch 4/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2063 - acc: 0.9769Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.2064 - acc: 0.9769 - val_loss: 1.7214 - val_acc: 0.8575
Epoch 5/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1918 - acc: 0.9775Epoch 00005: val_loss improved from 1.70679 to 1.64211, saving model to saved_models2/weights.best.ResNet_bs37_ep55.hdf5
6680/6680 [==============================] - 4s 534us/step - loss: 0.1907 - acc: 0.9777 - val_loss: 1.6421 - val_acc: 0.8647
Epoch 6/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1771 - acc: 0.9781Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1819 - acc: 0.9778 - val_loss: 1.6608 - val_acc: 0.8599
Epoch 7/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1619 - acc: 0.9827Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1618 - acc: 0.9822 - val_loss: 1.7832 - val_acc: 0.8575
Epoch 8/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1802 - acc: 0.9795Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 521us/step - loss: 0.1806 - acc: 0.9792 - val_loss: 1.6746 - val_acc: 0.8551
Epoch 9/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1680 - acc: 0.9798Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1679 - acc: 0.9798 - val_loss: 1.7220 - val_acc: 0.8563
Epoch 10/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1969 - acc: 0.9760Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1984 - acc: 0.9759 - val_loss: 1.7086 - val_acc: 0.8563
Epoch 11/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1810 - acc: 0.9783Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.1846 - acc: 0.9780 - val_loss: 1.7302 - val_acc: 0.8563
Epoch 12/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1880 - acc: 0.9772Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 4s 524us/step - loss: 0.1891 - acc: 0.9771 - val_loss: 1.6585 - val_acc: 0.8623
Epoch 13/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2039 - acc: 0.9760Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 4s 526us/step - loss: 0.2052 - acc: 0.9757 - val_loss: 1.6768 - val_acc: 0.8671
Epoch 14/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1983 - acc: 0.9762Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1955 - acc: 0.9765 - val_loss: 1.7455 - val_acc: 0.8587
Epoch 15/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1758 - acc: 0.9778Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1777 - acc: 0.9777 - val_loss: 1.7022 - val_acc: 0.8695
Epoch 16/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1725 - acc: 0.9789Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1728 - acc: 0.9787 - val_loss: 1.7201 - val_acc: 0.8659
Epoch 17/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1611 - acc: 0.9797Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 4s 527us/step - loss: 0.1593 - acc: 0.9798 - val_loss: 1.7958 - val_acc: 0.8491
Epoch 18/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1863 - acc: 0.9778Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1847 - acc: 0.9780 - val_loss: 1.8531 - val_acc: 0.8491
Epoch 19/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2136 - acc: 0.9775Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2150 - acc: 0.9775 - val_loss: 1.7493 - val_acc: 0.8539
Epoch 20/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1952 - acc: 0.9779Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1946 - acc: 0.9780 - val_loss: 1.7658 - val_acc: 0.8587
Epoch 21/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1800 - acc: 0.9801Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1774 - acc: 0.9804 - val_loss: 1.7251 - val_acc: 0.8575
Epoch 22/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1663 - acc: 0.9794Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 521us/step - loss: 0.1702 - acc: 0.9789 - val_loss: 1.7634 - val_acc: 0.8599
Epoch 23/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1931 - acc: 0.9790Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.1951 - acc: 0.9789 - val_loss: 1.7471 - val_acc: 0.8575
Epoch 24/55
6623/6680 [============================>.] - ETA: 0s - loss: 0.2131 - acc: 0.9760Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.2121 - acc: 0.9760 - val_loss: 1.7049 - val_acc: 0.8539
Epoch 25/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2002 - acc: 0.9775Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.2041 - acc: 0.9771 - val_loss: 1.7678 - val_acc: 0.8551
Epoch 26/55
6623/6680 [============================>.] - ETA: 0s - loss: 0.1690 - acc: 0.9807Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1676 - acc: 0.9808 - val_loss: 1.7422 - val_acc: 0.8587
Epoch 27/55
6660/6680 [============================>.] - ETA: 0s - loss: 0.1964 - acc: 0.9763Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1958 - acc: 0.9763 - val_loss: 1.7390 - val_acc: 0.8515
Epoch 28/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1691 - acc: 0.9810Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1690 - acc: 0.9808 - val_loss: 1.6803 - val_acc: 0.8587
Epoch 29/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1747 - acc: 0.9794Epoch 00029: val_loss improved from 1.64211 to 1.63743, saving model to saved_models2/weights.best.ResNet_bs37_ep55.hdf5
6680/6680 [==============================] - 4s 528us/step - loss: 0.1723 - acc: 0.9796 - val_loss: 1.6374 - val_acc: 0.8611
Epoch 30/55
6623/6680 [============================>.] - ETA: 0s - loss: 0.1777 - acc: 0.9799Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 4s 534us/step - loss: 0.1772 - acc: 0.9798 - val_loss: 1.8212 - val_acc: 0.8539
Epoch 31/55
6623/6680 [============================>.] - ETA: 0s - loss: 0.2054 - acc: 0.9766Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.2041 - acc: 0.9766 - val_loss: 1.7776 - val_acc: 0.8563
Epoch 32/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1846 - acc: 0.9780Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1903 - acc: 0.9775 - val_loss: 1.7635 - val_acc: 0.8623
Epoch 33/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1721 - acc: 0.9809Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1697 - acc: 0.9811 - val_loss: 1.8039 - val_acc: 0.8587
Epoch 34/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1634 - acc: 0.9819Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1660 - acc: 0.9819 - val_loss: 1.7976 - val_acc: 0.8563
Epoch 35/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1629 - acc: 0.9812Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 524us/step - loss: 0.1618 - acc: 0.9813 - val_loss: 1.7568 - val_acc: 0.8551
Epoch 36/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1969 - acc: 0.9787Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 4s 538us/step - loss: 0.1965 - acc: 0.9789 - val_loss: 1.7379 - val_acc: 0.8599
Epoch 37/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1894 - acc: 0.9784Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 4s 540us/step - loss: 0.1891 - acc: 0.9786 - val_loss: 1.8782 - val_acc: 0.8515
Epoch 38/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1910 - acc: 0.9783Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 4s 539us/step - loss: 0.1940 - acc: 0.9781 - val_loss: 1.8125 - val_acc: 0.8599
Epoch 39/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.9800Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1657 - acc: 0.9801 - val_loss: 1.8360 - val_acc: 0.8515
Epoch 40/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1595 - acc: 0.9813Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 4s 535us/step - loss: 0.1573 - acc: 0.9816 - val_loss: 1.8390 - val_acc: 0.8575
Epoch 41/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1668 - acc: 0.9813Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 4s 529us/step - loss: 0.1686 - acc: 0.9811 - val_loss: 1.7207 - val_acc: 0.8683
Epoch 42/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2391 - acc: 0.9753Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 3s 523us/step - loss: 0.2367 - acc: 0.9753 - val_loss: 1.7783 - val_acc: 0.8551
Epoch 43/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1705 - acc: 0.9804Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1681 - acc: 0.9807 - val_loss: 1.7614 - val_acc: 0.8647
Epoch 44/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1610 - acc: 0.9827Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1676 - acc: 0.9822 - val_loss: 1.8288 - val_acc: 0.8587
Epoch 45/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1434 - acc: 0.9851Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 4s 530us/step - loss: 0.1464 - acc: 0.9849 - val_loss: 1.7054 - val_acc: 0.8587
Epoch 46/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1539 - acc: 0.9810Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1518 - acc: 0.9813 - val_loss: 1.7149 - val_acc: 0.8647
Epoch 47/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1698 - acc: 0.9818Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 4s 536us/step - loss: 0.1703 - acc: 0.9816 - val_loss: 1.7665 - val_acc: 0.8623
Epoch 48/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1808 - acc: 0.9783Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1841 - acc: 0.9781 - val_loss: 1.8904 - val_acc: 0.8611
Epoch 49/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.2021 - acc: 0.9783Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.2018 - acc: 0.9783 - val_loss: 1.7805 - val_acc: 0.8599
Epoch 50/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1741 - acc: 0.9800Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 4s 528us/step - loss: 0.1770 - acc: 0.9796 - val_loss: 1.8164 - val_acc: 0.8575
Epoch 51/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1584 - acc: 0.9818Epoch 00051: val_loss did not improve
6680/6680 [==============================] - 4s 525us/step - loss: 0.1607 - acc: 0.9816 - val_loss: 1.7474 - val_acc: 0.8599
Epoch 52/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1666 - acc: 0.9819Epoch 00052: val_loss did not improve
6680/6680 [==============================] - 4s 531us/step - loss: 0.1696 - acc: 0.9817 - val_loss: 1.7698 - val_acc: 0.8659
Epoch 53/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1841 - acc: 0.9795Epoch 00053: val_loss did not improve
6680/6680 [==============================] - 4s 532us/step - loss: 0.1841 - acc: 0.9795 - val_loss: 1.8455 - val_acc: 0.8575
Epoch 54/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1898 - acc: 0.9803Epoch 00054: val_loss did not improve
6680/6680 [==============================] - 4s 533us/step - loss: 0.1901 - acc: 0.9802 - val_loss: 1.8572 - val_acc: 0.8539
Epoch 55/55
6586/6680 [============================>.] - ETA: 0s - loss: 0.1798 - acc: 0.9801Epoch 00055: val_loss did not improve
6680/6680 [==============================] - 3s 524us/step - loss: 0.1807 - acc: 0.9801 - val_loss: 1.7960 - val_acc: 0.8551

Batch size=40 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1636 - acc: 0.9795Epoch 00001: val_loss improved from inf to 1.65063, saving model to saved_models2/weights.best.ResNet_bs40_ep35.hdf5
6680/6680 [==============================] - 4s 527us/step - loss: 0.1633 - acc: 0.9793 - val_loss: 1.6506 - val_acc: 0.8587
Epoch 2/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1646 - acc: 0.9804Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1636 - acc: 0.9805 - val_loss: 1.7771 - val_acc: 0.8599
Epoch 3/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1544 - acc: 0.9810Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1535 - acc: 0.9811 - val_loss: 1.7631 - val_acc: 0.8635
Epoch 4/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1786 - acc: 0.9798Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 514us/step - loss: 0.1775 - acc: 0.9799 - val_loss: 1.8020 - val_acc: 0.8563
Epoch 5/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1872 - acc: 0.9779Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 519us/step - loss: 0.1887 - acc: 0.9777 - val_loss: 1.8268 - val_acc: 0.8527
Epoch 6/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1673 - acc: 0.9825Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1664 - acc: 0.9826 - val_loss: 1.8131 - val_acc: 0.8575
Epoch 7/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1683 - acc: 0.9803Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1693 - acc: 0.9802 - val_loss: 1.7990 - val_acc: 0.8575
Epoch 8/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1718 - acc: 0.9794Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1707 - acc: 0.9795 - val_loss: 1.7716 - val_acc: 0.8587
Epoch 9/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1957 - acc: 0.9783Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1965 - acc: 0.9783 - val_loss: 1.8416 - val_acc: 0.8539
Epoch 10/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1651 - acc: 0.9807Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1641 - acc: 0.9808 - val_loss: 1.8931 - val_acc: 0.8575
Epoch 11/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1755 - acc: 0.9791Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1760 - acc: 0.9790 - val_loss: 1.7870 - val_acc: 0.8647
Epoch 12/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1674 - acc: 0.9810Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1664 - acc: 0.9811 - val_loss: 1.7707 - val_acc: 0.8575
Epoch 13/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1730 - acc: 0.9812Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1744 - acc: 0.9811 - val_loss: 1.9160 - val_acc: 0.8527
Epoch 14/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1302 - acc: 0.9834Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1294 - acc: 0.9835 - val_loss: 1.7822 - val_acc: 0.8539
Epoch 15/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1979 - acc: 0.9801Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.2017 - acc: 0.9798 - val_loss: 1.7164 - val_acc: 0.8647
Epoch 16/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1896 - acc: 0.9783Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 518us/step - loss: 0.1886 - acc: 0.9783 - val_loss: 1.8609 - val_acc: 0.8563
Epoch 17/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.2090 - acc: 0.9783Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.2102 - acc: 0.9783 - val_loss: 1.7558 - val_acc: 0.8599
Epoch 18/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1727 - acc: 0.9792Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1717 - acc: 0.9793 - val_loss: 1.7393 - val_acc: 0.8623
Epoch 19/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1721 - acc: 0.9804Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1721 - acc: 0.9804 - val_loss: 1.8257 - val_acc: 0.8527
Epoch 20/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1866 - acc: 0.9801Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1855 - acc: 0.9802 - val_loss: 1.8835 - val_acc: 0.8575
Epoch 21/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1883 - acc: 0.9788Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1873 - acc: 0.9787 - val_loss: 1.8583 - val_acc: 0.8527
Epoch 22/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1967 - acc: 0.9786Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1955 - acc: 0.9787 - val_loss: 1.8432 - val_acc: 0.8539
Epoch 23/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1880 - acc: 0.9801Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1869 - acc: 0.9802 - val_loss: 1.8658 - val_acc: 0.8515
Epoch 24/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1685 - acc: 0.9807Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1675 - acc: 0.9808 - val_loss: 1.8197 - val_acc: 0.8563
Epoch 25/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1522 - acc: 0.9824Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1513 - acc: 0.9825 - val_loss: 1.8538 - val_acc: 0.8527
Epoch 26/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1464 - acc: 0.9830Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1467 - acc: 0.9829 - val_loss: 1.8367 - val_acc: 0.8599
Epoch 27/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1678 - acc: 0.9816Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1717 - acc: 0.9814 - val_loss: 1.8249 - val_acc: 0.8623
Epoch 28/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1557 - acc: 0.9827Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1557 - acc: 0.9826 - val_loss: 1.9023 - val_acc: 0.8575
Epoch 29/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1675 - acc: 0.9804Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1672 - acc: 0.9804 - val_loss: 1.9087 - val_acc: 0.8455
Epoch 30/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1629 - acc: 0.9822Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1643 - acc: 0.9822 - val_loss: 1.8870 - val_acc: 0.8611
Epoch 31/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1438 - acc: 0.9831Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1432 - acc: 0.9831 - val_loss: 1.9171 - val_acc: 0.8587
Epoch 32/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1633 - acc: 0.9824Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1624 - acc: 0.9825 - val_loss: 1.8538 - val_acc: 0.8587
Epoch 33/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1498 - acc: 0.9834Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1489 - acc: 0.9835 - val_loss: 1.9010 - val_acc: 0.8575
Epoch 34/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1831 - acc: 0.9812Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1820 - acc: 0.9813 - val_loss: 1.8673 - val_acc: 0.8503
Epoch 35/35
6640/6680 [============================>.] - ETA: 0s - loss: 0.1606 - acc: 0.9830Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1596 - acc: 0.9831 - val_loss: 1.9221 - val_acc: 0.8599

Batch size=40 Epoch=37
Train on 6680 samples, validate on 835 samples
Epoch 1/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9786Epoch 00001: val_loss improved from inf to 1.69151, saving model to saved_models2/weights.best.ResNet_bs40_ep37.hdf5
6680/6680 [==============================] - 3s 514us/step - loss: 0.1843 - acc: 0.9786 - val_loss: 1.6915 - val_acc: 0.8563
Epoch 2/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1838 - acc: 0.9800Epoch 00002: val_loss improved from 1.69151 to 1.67417, saving model to saved_models2/weights.best.ResNet_bs40_ep37.hdf5
6680/6680 [==============================] - 3s 508us/step - loss: 0.1837 - acc: 0.9798 - val_loss: 1.6742 - val_acc: 0.8599
Epoch 3/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1729 - acc: 0.9797Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1718 - acc: 0.9798 - val_loss: 1.7483 - val_acc: 0.8575
Epoch 4/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1612 - acc: 0.9800Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1629 - acc: 0.9798 - val_loss: 1.7521 - val_acc: 0.8563
Epoch 5/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1605 - acc: 0.9815Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1595 - acc: 0.9816 - val_loss: 1.7362 - val_acc: 0.8551
Epoch 6/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1466 - acc: 0.9815Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1467 - acc: 0.9814 - val_loss: 1.7812 - val_acc: 0.8599
Epoch 7/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1590 - acc: 0.9825Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1605 - acc: 0.9825 - val_loss: 1.7164 - val_acc: 0.8587
Epoch 8/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1742 - acc: 0.9803Epoch 00008: val_loss improved from 1.67417 to 1.67072, saving model to saved_models2/weights.best.ResNet_bs40_ep37.hdf5
6680/6680 [==============================] - 3s 513us/step - loss: 0.1744 - acc: 0.9801 - val_loss: 1.6707 - val_acc: 0.8671
Epoch 9/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1756 - acc: 0.9813Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1746 - acc: 0.9814 - val_loss: 1.7530 - val_acc: 0.8635
Epoch 10/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1508 - acc: 0.9825Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1499 - acc: 0.9826 - val_loss: 1.7288 - val_acc: 0.8527
Epoch 11/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1601 - acc: 0.9806Epoch 00011: val_loss improved from 1.67072 to 1.66728, saving model to saved_models2/weights.best.ResNet_bs40_ep37.hdf5
6680/6680 [==============================] - 3s 511us/step - loss: 0.1592 - acc: 0.9807 - val_loss: 1.6673 - val_acc: 0.8635
Epoch 12/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1625 - acc: 0.9821Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1615 - acc: 0.9822 - val_loss: 1.7624 - val_acc: 0.8539
Epoch 13/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1473 - acc: 0.9825Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1489 - acc: 0.9825 - val_loss: 1.7514 - val_acc: 0.8551
Epoch 14/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1642 - acc: 0.9810Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1632 - acc: 0.9811 - val_loss: 1.7240 - val_acc: 0.8527
Epoch 15/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1728 - acc: 0.9801Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1729 - acc: 0.9801 - val_loss: 1.7907 - val_acc: 0.8491
Epoch 16/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1954 - acc: 0.9794Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1942 - acc: 0.9795 - val_loss: 1.8802 - val_acc: 0.8479
Epoch 17/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1890 - acc: 0.9795Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1886 - acc: 0.9795 - val_loss: 1.9013 - val_acc: 0.8431
Epoch 18/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1599 - acc: 0.9819Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1591 - acc: 0.9819 - val_loss: 1.8346 - val_acc: 0.8479
Epoch 19/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1613 - acc: 0.9803Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1603 - acc: 0.9804 - val_loss: 1.8367 - val_acc: 0.8515
Epoch 20/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1550 - acc: 0.9803Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1554 - acc: 0.9802 - val_loss: 1.8498 - val_acc: 0.8407
Epoch 21/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1732 - acc: 0.9795Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1727 - acc: 0.9795 - val_loss: 1.9020 - val_acc: 0.8455
Epoch 22/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1710 - acc: 0.9810Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1700 - acc: 0.9811 - val_loss: 1.8482 - val_acc: 0.8515
Epoch 23/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1599 - acc: 0.9798Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1589 - acc: 0.9799 - val_loss: 1.8940 - val_acc: 0.8443
Epoch 24/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1673 - acc: 0.9803Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1663 - acc: 0.9804 - val_loss: 1.9267 - val_acc: 0.8395
Epoch 25/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1623 - acc: 0.9804Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1637 - acc: 0.9804 - val_loss: 1.9226 - val_acc: 0.8455
Epoch 26/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1797 - acc: 0.9794Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1788 - acc: 0.9793 - val_loss: 1.8297 - val_acc: 0.8479
Epoch 27/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1331 - acc: 0.9837Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1323 - acc: 0.9838 - val_loss: 1.8138 - val_acc: 0.8539
Epoch 28/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1908 - acc: 0.9798Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1897 - acc: 0.9799 - val_loss: 1.8526 - val_acc: 0.8575
Epoch 29/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1552 - acc: 0.9827Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1564 - acc: 0.9825 - val_loss: 1.8998 - val_acc: 0.8575
Epoch 30/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9782Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1840 - acc: 0.9780 - val_loss: 1.9335 - val_acc: 0.8467
Epoch 31/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1406 - acc: 0.9839Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1397 - acc: 0.9840 - val_loss: 1.8205 - val_acc: 0.8455
Epoch 32/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1799 - acc: 0.9804Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1794 - acc: 0.9804 - val_loss: 1.9292 - val_acc: 0.8515
Epoch 33/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1591 - acc: 0.9839Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1581 - acc: 0.9840 - val_loss: 1.9346 - val_acc: 0.8491
Epoch 34/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1682 - acc: 0.9801Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1673 - acc: 0.9802 - val_loss: 1.8556 - val_acc: 0.8527
Epoch 35/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1587 - acc: 0.9822Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1609 - acc: 0.9820 - val_loss: 1.8426 - val_acc: 0.8575
Epoch 36/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1326 - acc: 0.9839Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1342 - acc: 0.9838 - val_loss: 1.8166 - val_acc: 0.8599
Epoch 37/37
6640/6680 [============================>.] - ETA: 0s - loss: 0.1583 - acc: 0.9822Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1574 - acc: 0.9823 - val_loss: 1.9435 - val_acc: 0.8515

Batch size=40 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1684 - acc: 0.9813Epoch 00001: val_loss improved from inf to 1.66598, saving model to saved_models2/weights.best.ResNet_bs40_ep40.hdf5
6680/6680 [==============================] - 3s 506us/step - loss: 0.1673 - acc: 0.9814 - val_loss: 1.6660 - val_acc: 0.8623
Epoch 2/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1761 - acc: 0.9794Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1755 - acc: 0.9793 - val_loss: 1.7194 - val_acc: 0.8671
Epoch 3/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1552 - acc: 0.9812Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 517us/step - loss: 0.1558 - acc: 0.9811 - val_loss: 1.7532 - val_acc: 0.8587
Epoch 4/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1655 - acc: 0.9810Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1663 - acc: 0.9810 - val_loss: 1.8292 - val_acc: 0.8539
Epoch 5/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1910 - acc: 0.9788Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1898 - acc: 0.9789 - val_loss: 1.8116 - val_acc: 0.8503
Epoch 6/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1619 - acc: 0.9822Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1614 - acc: 0.9822 - val_loss: 1.8134 - val_acc: 0.8587
Epoch 7/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1455 - acc: 0.9824Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1446 - acc: 0.9825 - val_loss: 1.8291 - val_acc: 0.8503
Epoch 8/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.2012 - acc: 0.9783Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.2000 - acc: 0.9784 - val_loss: 1.8148 - val_acc: 0.8551
Epoch 9/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1882 - acc: 0.9786Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1871 - acc: 0.9787 - val_loss: 1.8112 - val_acc: 0.8587
Epoch 10/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1387 - acc: 0.9828Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1379 - acc: 0.9829 - val_loss: 1.8388 - val_acc: 0.8539
Epoch 11/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1671 - acc: 0.9809Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1662 - acc: 0.9810 - val_loss: 1.7909 - val_acc: 0.8587
Epoch 12/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1885 - acc: 0.9777Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1895 - acc: 0.9777 - val_loss: 1.9115 - val_acc: 0.8491
Epoch 13/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1620 - acc: 0.9816Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1614 - acc: 0.9816 - val_loss: 1.8494 - val_acc: 0.8539
Epoch 14/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1690 - acc: 0.9810Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1733 - acc: 0.9807 - val_loss: 1.8676 - val_acc: 0.8515
Epoch 15/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1444 - acc: 0.9831Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1436 - acc: 0.9832 - val_loss: 1.9150 - val_acc: 0.8527
Epoch 16/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1677 - acc: 0.9816Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1691 - acc: 0.9816 - val_loss: 1.8358 - val_acc: 0.8539
Epoch 17/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1608 - acc: 0.9806Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1598 - acc: 0.9807 - val_loss: 1.7637 - val_acc: 0.8599
Epoch 18/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1540 - acc: 0.9824Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1531 - acc: 0.9825 - val_loss: 1.8372 - val_acc: 0.8587
Epoch 19/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1559 - acc: 0.9816Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1574 - acc: 0.9816 - val_loss: 1.8471 - val_acc: 0.8539
Epoch 20/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1776 - acc: 0.9800Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1789 - acc: 0.9799 - val_loss: 1.9047 - val_acc: 0.8503
Epoch 21/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1670 - acc: 0.9797Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1686 - acc: 0.9795 - val_loss: 1.9780 - val_acc: 0.8491
Epoch 22/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1519 - acc: 0.9833Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1521 - acc: 0.9832 - val_loss: 1.9177 - val_acc: 0.8527
Epoch 23/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1598 - acc: 0.9821Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1588 - acc: 0.9822 - val_loss: 1.8832 - val_acc: 0.8539
Epoch 24/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1640 - acc: 0.9816Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1658 - acc: 0.9814 - val_loss: 1.9027 - val_acc: 0.8515
Epoch 25/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1510 - acc: 0.9825Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1501 - acc: 0.9826 - val_loss: 1.8784 - val_acc: 0.8503
Epoch 26/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1614 - acc: 0.9816Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1604 - acc: 0.9817 - val_loss: 1.9459 - val_acc: 0.8503
Epoch 27/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1591 - acc: 0.9824Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1581 - acc: 0.9825 - val_loss: 1.9514 - val_acc: 0.8479
Epoch 28/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1698 - acc: 0.9818Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1688 - acc: 0.9819 - val_loss: 1.9780 - val_acc: 0.8455
Epoch 29/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1810 - acc: 0.9807Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1799 - acc: 0.9808 - val_loss: 1.9489 - val_acc: 0.8455
Epoch 30/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1566 - acc: 0.9810Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1567 - acc: 0.9810 - val_loss: 1.9872 - val_acc: 0.8467
Epoch 31/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1584 - acc: 0.9827Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1574 - acc: 0.9828 - val_loss: 1.9291 - val_acc: 0.8455
Epoch 32/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1556 - acc: 0.9827Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1547 - acc: 0.9828 - val_loss: 2.0061 - val_acc: 0.8431
Epoch 33/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1867 - acc: 0.9815Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 517us/step - loss: 0.1880 - acc: 0.9814 - val_loss: 1.8879 - val_acc: 0.8539
Epoch 34/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1736 - acc: 0.9819Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1749 - acc: 0.9819 - val_loss: 1.9445 - val_acc: 0.8467
Epoch 35/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1611 - acc: 0.9815Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1612 - acc: 0.9814 - val_loss: 1.8904 - val_acc: 0.8551
Epoch 36/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1934 - acc: 0.9804Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1922 - acc: 0.9805 - val_loss: 1.9146 - val_acc: 0.8515
Epoch 37/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1235 - acc: 0.9857Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1257 - acc: 0.9855 - val_loss: 1.8853 - val_acc: 0.8527
Epoch 38/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1511 - acc: 0.9831Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1502 - acc: 0.9832 - val_loss: 1.9265 - val_acc: 0.8587
Epoch 39/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1486 - acc: 0.9849Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1478 - acc: 0.9850 - val_loss: 1.8337 - val_acc: 0.8575
Epoch 40/40
6640/6680 [============================>.] - ETA: 0s - loss: 0.1430 - acc: 0.9821Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1421 - acc: 0.9822 - val_loss: 1.9012 - val_acc: 0.8611

Batch size=40 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1606 - acc: 0.9801Epoch 00001: val_loss improved from inf to 1.69763, saving model to saved_models2/weights.best.ResNet_bs40_ep50.hdf5
6680/6680 [==============================] - 3s 512us/step - loss: 0.1612 - acc: 0.9801 - val_loss: 1.6976 - val_acc: 0.8623
Epoch 2/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1546 - acc: 0.9813Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1572 - acc: 0.9811 - val_loss: 1.7130 - val_acc: 0.8635
Epoch 3/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1501 - acc: 0.9822Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1495 - acc: 0.9822 - val_loss: 1.8132 - val_acc: 0.8551
Epoch 4/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1669 - acc: 0.9813Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1699 - acc: 0.9808 - val_loss: 1.7761 - val_acc: 0.8611
Epoch 5/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1725 - acc: 0.9800Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1715 - acc: 0.9801 - val_loss: 1.7199 - val_acc: 0.8551
Epoch 6/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1798 - acc: 0.9791Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1812 - acc: 0.9790 - val_loss: 1.8126 - val_acc: 0.8491
Epoch 7/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1775 - acc: 0.9792Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1764 - acc: 0.9793 - val_loss: 1.7861 - val_acc: 0.8587
Epoch 8/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1587 - acc: 0.9834Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1578 - acc: 0.9835 - val_loss: 1.8082 - val_acc: 0.8575
Epoch 9/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1877 - acc: 0.9789Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1866 - acc: 0.9790 - val_loss: 1.8685 - val_acc: 0.8527
Epoch 10/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1872 - acc: 0.9800Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1862 - acc: 0.9799 - val_loss: 1.8273 - val_acc: 0.8539
Epoch 11/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1800 - acc: 0.9795Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1790 - acc: 0.9796 - val_loss: 1.8297 - val_acc: 0.8623
Epoch 12/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1670 - acc: 0.9819Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1707 - acc: 0.9816 - val_loss: 1.7558 - val_acc: 0.8587
Epoch 13/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1728 - acc: 0.9798Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1738 - acc: 0.9798 - val_loss: 1.8261 - val_acc: 0.8599
Epoch 14/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.2064 - acc: 0.9783Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.2065 - acc: 0.9781 - val_loss: 1.8061 - val_acc: 0.8575
Epoch 15/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1855 - acc: 0.9782Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1860 - acc: 0.9781 - val_loss: 1.7849 - val_acc: 0.8623
Epoch 16/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1491 - acc: 0.9830Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1482 - acc: 0.9831 - val_loss: 1.7349 - val_acc: 0.8647
Epoch 17/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1546 - acc: 0.9828Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1537 - acc: 0.9829 - val_loss: 1.7691 - val_acc: 0.8623
Epoch 18/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1466 - acc: 0.9809Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1460 - acc: 0.9808 - val_loss: 1.7732 - val_acc: 0.8611
Epoch 19/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1603 - acc: 0.9821Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1593 - acc: 0.9822 - val_loss: 1.8276 - val_acc: 0.8599
Epoch 20/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1422 - acc: 0.9828Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1450 - acc: 0.9826 - val_loss: 1.8654 - val_acc: 0.8515
Epoch 21/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1481 - acc: 0.9827Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1496 - acc: 0.9826 - val_loss: 1.8728 - val_acc: 0.8551
Epoch 22/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1596 - acc: 0.9822Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1630 - acc: 0.9819 - val_loss: 1.7234 - val_acc: 0.8599
Epoch 23/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1427 - acc: 0.9839Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1419 - acc: 0.9840 - val_loss: 1.7289 - val_acc: 0.8599
Epoch 24/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1695 - acc: 0.9830Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1685 - acc: 0.9831 - val_loss: 1.7757 - val_acc: 0.8611
Epoch 25/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.9818Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1646 - acc: 0.9819 - val_loss: 1.7789 - val_acc: 0.8539
Epoch 26/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1461 - acc: 0.9801Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1473 - acc: 0.9801 - val_loss: 1.7190 - val_acc: 0.8659
Epoch 27/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1905 - acc: 0.9794Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1908 - acc: 0.9793 - val_loss: 1.7700 - val_acc: 0.8599
Epoch 28/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1735 - acc: 0.9807Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1725 - acc: 0.9808 - val_loss: 1.7738 - val_acc: 0.8611
Epoch 29/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1510 - acc: 0.9836Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1526 - acc: 0.9835 - val_loss: 1.7690 - val_acc: 0.8659
Epoch 30/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1620 - acc: 0.9819Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1610 - acc: 0.9820 - val_loss: 1.8384 - val_acc: 0.8623
Epoch 31/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1536 - acc: 0.9821Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1551 - acc: 0.9820 - val_loss: 1.8316 - val_acc: 0.8575
Epoch 32/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1827 - acc: 0.9795Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1816 - acc: 0.9796 - val_loss: 1.7674 - val_acc: 0.8599
Epoch 33/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1700 - acc: 0.9809Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1690 - acc: 0.9810 - val_loss: 1.8325 - val_acc: 0.8551
Epoch 34/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1501 - acc: 0.9836Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1492 - acc: 0.9837 - val_loss: 1.8586 - val_acc: 0.8563
Epoch 35/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1715 - acc: 0.9816Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1705 - acc: 0.9816 - val_loss: 1.8567 - val_acc: 0.8443
Epoch 36/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1801 - acc: 0.9810Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1814 - acc: 0.9810 - val_loss: 1.8360 - val_acc: 0.8515
Epoch 37/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1788 - acc: 0.9798Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1778 - acc: 0.9799 - val_loss: 1.8312 - val_acc: 0.8575
Epoch 38/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1684 - acc: 0.9818Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1675 - acc: 0.9817 - val_loss: 1.8053 - val_acc: 0.8599
Epoch 39/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1914 - acc: 0.9789Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1902 - acc: 0.9790 - val_loss: 1.7880 - val_acc: 0.8539
Epoch 40/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1661 - acc: 0.9806Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1652 - acc: 0.9807 - val_loss: 1.7280 - val_acc: 0.8599
Epoch 41/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1657 - acc: 0.9812Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 3s 517us/step - loss: 0.1647 - acc: 0.9813 - val_loss: 1.8008 - val_acc: 0.8599
Epoch 42/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1812 - acc: 0.9806Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1801 - acc: 0.9807 - val_loss: 1.8285 - val_acc: 0.8563
Epoch 43/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1363 - acc: 0.9846Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1360 - acc: 0.9846 - val_loss: 1.8122 - val_acc: 0.8659
Epoch 44/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1789 - acc: 0.9806Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 3s 515us/step - loss: 0.1778 - acc: 0.9807 - val_loss: 1.8308 - val_acc: 0.8587
Epoch 45/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1495 - acc: 0.9842Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1486 - acc: 0.9843 - val_loss: 1.8587 - val_acc: 0.8587
Epoch 46/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1786 - acc: 0.9812Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1792 - acc: 0.9811 - val_loss: 1.9461 - val_acc: 0.8515
Epoch 47/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1561 - acc: 0.9828Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1552 - acc: 0.9829 - val_loss: 1.9783 - val_acc: 0.8527
Epoch 48/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1585 - acc: 0.9830Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1576 - acc: 0.9831 - val_loss: 1.8344 - val_acc: 0.8503
Epoch 49/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1326 - acc: 0.9827Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1350 - acc: 0.9825 - val_loss: 1.8573 - val_acc: 0.8611
Epoch 50/50
6640/6680 [============================>.] - ETA: 0s - loss: 0.1520 - acc: 0.9833Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1530 - acc: 0.9832 - val_loss: 1.8341 - val_acc: 0.8527

Batch size=40 Epoch=55
Train on 6680 samples, validate on 835 samples
Epoch 1/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1640 - acc: 0.9809Epoch 00001: val_loss improved from inf to 1.71222, saving model to saved_models2/weights.best.ResNet_bs40_ep55.hdf5
6680/6680 [==============================] - 3s 516us/step - loss: 0.1633 - acc: 0.9808 - val_loss: 1.7122 - val_acc: 0.8623
Epoch 2/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1723 - acc: 0.9800Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 514us/step - loss: 0.1737 - acc: 0.9799 - val_loss: 1.7469 - val_acc: 0.8647
Epoch 3/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1649 - acc: 0.9807Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1639 - acc: 0.9808 - val_loss: 1.7621 - val_acc: 0.8539
Epoch 4/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1821 - acc: 0.9792Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1835 - acc: 0.9790 - val_loss: 1.7132 - val_acc: 0.8635
Epoch 5/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1764 - acc: 0.9803Epoch 00005: val_loss improved from 1.71222 to 1.70566, saving model to saved_models2/weights.best.ResNet_bs40_ep55.hdf5
6680/6680 [==============================] - 3s 515us/step - loss: 0.1754 - acc: 0.9804 - val_loss: 1.7057 - val_acc: 0.8599
Epoch 6/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1774 - acc: 0.9795Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1763 - acc: 0.9796 - val_loss: 1.7540 - val_acc: 0.8647
Epoch 7/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1670 - acc: 0.9819Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1684 - acc: 0.9819 - val_loss: 1.7696 - val_acc: 0.8647
Epoch 8/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1682 - acc: 0.9806Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1732 - acc: 0.9802 - val_loss: 1.8591 - val_acc: 0.8575
Epoch 9/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1593 - acc: 0.9816Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1584 - acc: 0.9817 - val_loss: 1.9046 - val_acc: 0.8527
Epoch 10/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1441 - acc: 0.9822Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1432 - acc: 0.9823 - val_loss: 1.8333 - val_acc: 0.8575
Epoch 11/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1797 - acc: 0.9809Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1787 - acc: 0.9810 - val_loss: 1.8047 - val_acc: 0.8587
Epoch 12/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1762 - acc: 0.9797Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1759 - acc: 0.9796 - val_loss: 1.8605 - val_acc: 0.8563
Epoch 13/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1490 - acc: 0.9825Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1534 - acc: 0.9822 - val_loss: 1.7914 - val_acc: 0.8599
Epoch 14/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1738 - acc: 0.9810Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1731 - acc: 0.9810 - val_loss: 1.8240 - val_acc: 0.8539
Epoch 15/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.2018 - acc: 0.9803Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.2006 - acc: 0.9804 - val_loss: 1.7969 - val_acc: 0.8575
Epoch 16/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1498 - acc: 0.9822Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1494 - acc: 0.9822 - val_loss: 1.9169 - val_acc: 0.8575
Epoch 17/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1799 - acc: 0.9804Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1788 - acc: 0.9805 - val_loss: 1.8616 - val_acc: 0.8587
Epoch 18/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1426 - acc: 0.9849Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1418 - acc: 0.9850 - val_loss: 1.8169 - val_acc: 0.8599
Epoch 19/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1505 - acc: 0.9812Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1496 - acc: 0.9813 - val_loss: 1.8052 - val_acc: 0.8563
Epoch 20/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1617 - acc: 0.9816Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1607 - acc: 0.9817 - val_loss: 1.8527 - val_acc: 0.8515
Epoch 21/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1963 - acc: 0.9767Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1975 - acc: 0.9766 - val_loss: 1.8605 - val_acc: 0.8539
Epoch 22/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1747 - acc: 0.9807Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1756 - acc: 0.9807 - val_loss: 1.7852 - val_acc: 0.8575
Epoch 23/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1882 - acc: 0.9794Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1871 - acc: 0.9795 - val_loss: 1.8928 - val_acc: 0.8575
Epoch 24/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1677 - acc: 0.9815Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1667 - acc: 0.9816 - val_loss: 1.8719 - val_acc: 0.8527
Epoch 25/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1827 - acc: 0.9797Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1816 - acc: 0.9798 - val_loss: 1.8076 - val_acc: 0.8587
Epoch 26/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1738 - acc: 0.9803Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1759 - acc: 0.9801 - val_loss: 1.7254 - val_acc: 0.8671
Epoch 27/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1616 - acc: 0.9816Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1606 - acc: 0.9817 - val_loss: 1.8117 - val_acc: 0.8623
Epoch 28/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1581 - acc: 0.9825Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 518us/step - loss: 0.1619 - acc: 0.9823 - val_loss: 1.7751 - val_acc: 0.8575
Epoch 29/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1437 - acc: 0.9810Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 520us/step - loss: 0.1444 - acc: 0.9810 - val_loss: 1.8158 - val_acc: 0.8647
Epoch 30/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1560 - acc: 0.9818Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 522us/step - loss: 0.1574 - acc: 0.9817 - val_loss: 1.8697 - val_acc: 0.8575
Epoch 31/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1593 - acc: 0.9830Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1606 - acc: 0.9829 - val_loss: 1.8149 - val_acc: 0.8551
Epoch 32/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1748 - acc: 0.9806Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1738 - acc: 0.9807 - val_loss: 1.9190 - val_acc: 0.8479
Epoch 33/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1505 - acc: 0.9833Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1496 - acc: 0.9834 - val_loss: 1.9040 - val_acc: 0.8455
Epoch 34/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1674 - acc: 0.9822Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1713 - acc: 0.9820 - val_loss: 1.8915 - val_acc: 0.8539
Epoch 35/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1849 - acc: 0.9807Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1862 - acc: 0.9807 - val_loss: 1.8822 - val_acc: 0.8575
Epoch 36/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1726 - acc: 0.9803Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1721 - acc: 0.9802 - val_loss: 1.8147 - val_acc: 0.8563
Epoch 37/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1403 - acc: 0.9846Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1395 - acc: 0.9847 - val_loss: 1.9024 - val_acc: 0.8563
Epoch 38/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1270 - acc: 0.9848Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1263 - acc: 0.9849 - val_loss: 1.8828 - val_acc: 0.8587
Epoch 39/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1783 - acc: 0.9807Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1797 - acc: 0.9807 - val_loss: 1.9087 - val_acc: 0.8587
Epoch 40/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.9809Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1677 - acc: 0.9805 - val_loss: 1.9354 - val_acc: 0.8551
Epoch 41/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1576 - acc: 0.9818Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1580 - acc: 0.9816 - val_loss: 1.8835 - val_acc: 0.8551
Epoch 42/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1627 - acc: 0.9819Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1621 - acc: 0.9819 - val_loss: 1.8344 - val_acc: 0.8563
Epoch 43/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1613 - acc: 0.9846Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1608 - acc: 0.9846 - val_loss: 1.9193 - val_acc: 0.8527
Epoch 44/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1647 - acc: 0.9807Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1662 - acc: 0.9807 - val_loss: 1.8708 - val_acc: 0.8539
Epoch 45/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1485 - acc: 0.9842Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1501 - acc: 0.9841 - val_loss: 1.9063 - val_acc: 0.8563
Epoch 46/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1396 - acc: 0.9839Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1388 - acc: 0.9840 - val_loss: 1.9169 - val_acc: 0.8539
Epoch 47/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1700 - acc: 0.9812Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1692 - acc: 0.9811 - val_loss: 1.8624 - val_acc: 0.8539
Epoch 48/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1420 - acc: 0.9846Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1412 - acc: 0.9847 - val_loss: 1.9382 - val_acc: 0.8515
Epoch 49/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1476 - acc: 0.9836Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1467 - acc: 0.9837 - val_loss: 1.8462 - val_acc: 0.8575
Epoch 50/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1336 - acc: 0.9843Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1328 - acc: 0.9844 - val_loss: 1.9065 - val_acc: 0.8539
Epoch 51/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1482 - acc: 0.9837Epoch 00051: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1508 - acc: 0.9835 - val_loss: 1.9052 - val_acc: 0.8527
Epoch 52/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1353 - acc: 0.9860Epoch 00052: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1355 - acc: 0.9859 - val_loss: 2.0075 - val_acc: 0.8503
Epoch 53/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1586 - acc: 0.9840Epoch 00053: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1601 - acc: 0.9840 - val_loss: 1.9596 - val_acc: 0.8563
Epoch 54/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1805 - acc: 0.9807Epoch 00054: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1796 - acc: 0.9807 - val_loss: 2.0263 - val_acc: 0.8479
Epoch 55/55
6640/6680 [============================>.] - ETA: 0s - loss: 0.1821 - acc: 0.9812Epoch 00055: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1834 - acc: 0.9811 - val_loss: 2.0401 - val_acc: 0.8491

Batch size=41 Epoch=35
Train on 6680 samples, validate on 835 samples
Epoch 1/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1645 - acc: 0.9814Epoch 00001: val_loss improved from inf to 1.64528, saving model to saved_models2/weights.best.ResNet_bs41_ep35.hdf5
6680/6680 [==============================] - 3s 507us/step - loss: 0.1664 - acc: 0.9814 - val_loss: 1.6453 - val_acc: 0.8599
Epoch 2/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1801 - acc: 0.9812Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1789 - acc: 0.9814 - val_loss: 1.7093 - val_acc: 0.8635
Epoch 3/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1812 - acc: 0.9791Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1780 - acc: 0.9795 - val_loss: 1.7455 - val_acc: 0.8623
Epoch 4/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1803 - acc: 0.9796Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1789 - acc: 0.9798 - val_loss: 1.7884 - val_acc: 0.8587
Epoch 5/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9802Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1849 - acc: 0.9801 - val_loss: 1.8356 - val_acc: 0.8563
Epoch 6/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1581 - acc: 0.9832Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1578 - acc: 0.9834 - val_loss: 1.7747 - val_acc: 0.8611
Epoch 7/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1819 - acc: 0.9791Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1820 - acc: 0.9790 - val_loss: 1.7909 - val_acc: 0.8515
Epoch 8/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1865 - acc: 0.9790Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1832 - acc: 0.9793 - val_loss: 1.8131 - val_acc: 0.8623
Epoch 9/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1533 - acc: 0.9841Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1559 - acc: 0.9840 - val_loss: 1.8358 - val_acc: 0.8575
Epoch 10/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1407 - acc: 0.9831Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1407 - acc: 0.9831 - val_loss: 1.7999 - val_acc: 0.8515
Epoch 11/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1954 - acc: 0.9790Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1920 - acc: 0.9793 - val_loss: 1.8035 - val_acc: 0.8539
Epoch 12/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1473 - acc: 0.9835Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1519 - acc: 0.9834 - val_loss: 1.8544 - val_acc: 0.8551
Epoch 13/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1947 - acc: 0.9785Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1914 - acc: 0.9787 - val_loss: 1.8587 - val_acc: 0.8527
Epoch 14/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1543 - acc: 0.9814Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1515 - acc: 0.9817 - val_loss: 1.9267 - val_acc: 0.8527
Epoch 15/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1498 - acc: 0.9837Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1522 - acc: 0.9835 - val_loss: 1.8691 - val_acc: 0.8599
Epoch 16/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1604 - acc: 0.9803Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1624 - acc: 0.9804 - val_loss: 1.8703 - val_acc: 0.8539
Epoch 17/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1499 - acc: 0.9849Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1552 - acc: 0.9846 - val_loss: 1.8261 - val_acc: 0.8563
Epoch 18/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1694 - acc: 0.9799Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1755 - acc: 0.9796 - val_loss: 1.7643 - val_acc: 0.8515
Epoch 19/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1915 - acc: 0.9802Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1895 - acc: 0.9802 - val_loss: 1.7363 - val_acc: 0.8575
Epoch 20/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1561 - acc: 0.9828Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1541 - acc: 0.9829 - val_loss: 1.7357 - val_acc: 0.8623
Epoch 21/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1684 - acc: 0.9799Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1670 - acc: 0.9799 - val_loss: 1.7545 - val_acc: 0.8599
Epoch 22/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1626 - acc: 0.9808Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1597 - acc: 0.9811 - val_loss: 1.7914 - val_acc: 0.8623
Epoch 23/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1514 - acc: 0.9819Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 489us/step - loss: 0.1487 - acc: 0.9822 - val_loss: 1.7705 - val_acc: 0.8623
Epoch 24/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1458 - acc: 0.9840Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1458 - acc: 0.9841 - val_loss: 1.7224 - val_acc: 0.8599
Epoch 25/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1633 - acc: 0.9823Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1653 - acc: 0.9822 - val_loss: 1.7762 - val_acc: 0.8611
Epoch 26/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1511 - acc: 0.9831Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1484 - acc: 0.9834 - val_loss: 1.7147 - val_acc: 0.8587
Epoch 27/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9829Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1574 - acc: 0.9828 - val_loss: 1.7932 - val_acc: 0.8623
Epoch 28/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1412 - acc: 0.9848Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1428 - acc: 0.9846 - val_loss: 1.7499 - val_acc: 0.8659
Epoch 29/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1652 - acc: 0.9828Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1723 - acc: 0.9822 - val_loss: 1.9082 - val_acc: 0.8563
Epoch 30/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1778 - acc: 0.9800Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1746 - acc: 0.9804 - val_loss: 1.7394 - val_acc: 0.8623
Epoch 31/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1662 - acc: 0.9820Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1657 - acc: 0.9822 - val_loss: 1.8042 - val_acc: 0.8599
Epoch 32/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1527 - acc: 0.9831Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 514us/step - loss: 0.1550 - acc: 0.9829 - val_loss: 1.8729 - val_acc: 0.8539
Epoch 33/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1476 - acc: 0.9848Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1493 - acc: 0.9844 - val_loss: 1.8252 - val_acc: 0.8515
Epoch 34/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1421 - acc: 0.9837Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1403 - acc: 0.9837 - val_loss: 1.8979 - val_acc: 0.8503
Epoch 35/35
6560/6680 [============================>.] - ETA: 0s - loss: 0.1868 - acc: 0.9806Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1860 - acc: 0.9807 - val_loss: 1.8104 - val_acc: 0.8611

Batch size=41 Epoch=37
Train on 6680 samples, validate on 835 samples
Epoch 1/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1662 - acc: 0.9817Epoch 00001: val_loss improved from inf to 1.77754, saving model to saved_models2/weights.best.ResNet_bs41_ep37.hdf5
6680/6680 [==============================] - 3s 509us/step - loss: 0.1657 - acc: 0.9817 - val_loss: 1.7775 - val_acc: 0.8527
Epoch 2/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9819Epoch 00002: val_loss improved from 1.77754 to 1.72016, saving model to saved_models2/weights.best.ResNet_bs41_ep37.hdf5
6680/6680 [==============================] - 3s 519us/step - loss: 0.1536 - acc: 0.9819 - val_loss: 1.7202 - val_acc: 0.8647
Epoch 3/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1794 - acc: 0.9790Epoch 00003: val_loss improved from 1.72016 to 1.65747, saving model to saved_models2/weights.best.ResNet_bs41_ep37.hdf5
6680/6680 [==============================] - 3s 514us/step - loss: 0.1810 - acc: 0.9790 - val_loss: 1.6575 - val_acc: 0.8635
Epoch 4/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1516 - acc: 0.9828Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1513 - acc: 0.9829 - val_loss: 1.7214 - val_acc: 0.8587
Epoch 5/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1833 - acc: 0.9791Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1833 - acc: 0.9792 - val_loss: 1.6589 - val_acc: 0.8587
Epoch 6/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9819Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1817 - acc: 0.9817 - val_loss: 1.7618 - val_acc: 0.8551
Epoch 7/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1814 - acc: 0.9797Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1782 - acc: 0.9801 - val_loss: 1.8323 - val_acc: 0.8491
Epoch 8/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1694 - acc: 0.9809Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1687 - acc: 0.9811 - val_loss: 1.7134 - val_acc: 0.8623
Epoch 9/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1508 - acc: 0.9820Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1506 - acc: 0.9822 - val_loss: 1.8212 - val_acc: 0.8491
Epoch 10/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1729 - acc: 0.9806Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1698 - acc: 0.9810 - val_loss: 1.8018 - val_acc: 0.8551
Epoch 11/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1687 - acc: 0.9811Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 515us/step - loss: 0.1687 - acc: 0.9811 - val_loss: 1.8171 - val_acc: 0.8503
Epoch 12/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1592 - acc: 0.9823Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1636 - acc: 0.9819 - val_loss: 1.8267 - val_acc: 0.8527
Epoch 13/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1190 - acc: 0.9851Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1206 - acc: 0.9850 - val_loss: 1.7853 - val_acc: 0.8599
Epoch 14/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1830 - acc: 0.9796Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1822 - acc: 0.9796 - val_loss: 1.8008 - val_acc: 0.8539
Epoch 15/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1588 - acc: 0.9823Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1601 - acc: 0.9820 - val_loss: 1.7627 - val_acc: 0.8563
Epoch 16/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1543 - acc: 0.9832Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1546 - acc: 0.9832 - val_loss: 1.8442 - val_acc: 0.8611
Epoch 17/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1538 - acc: 0.9825Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1536 - acc: 0.9825 - val_loss: 1.8406 - val_acc: 0.8491
Epoch 18/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.2001 - acc: 0.9788Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.2015 - acc: 0.9787 - val_loss: 1.8778 - val_acc: 0.8527
Epoch 19/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1685 - acc: 0.9817Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1693 - acc: 0.9816 - val_loss: 1.8517 - val_acc: 0.8515
Epoch 20/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1595 - acc: 0.9829Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1579 - acc: 0.9831 - val_loss: 1.8728 - val_acc: 0.8503
Epoch 21/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1771 - acc: 0.9811Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1794 - acc: 0.9810 - val_loss: 1.9372 - val_acc: 0.8515
Epoch 22/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1391 - acc: 0.9848Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1419 - acc: 0.9844 - val_loss: 1.8713 - val_acc: 0.8431
Epoch 23/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1725 - acc: 0.9805Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1748 - acc: 0.9802 - val_loss: 1.8276 - val_acc: 0.8551
Epoch 24/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1760 - acc: 0.9805Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1749 - acc: 0.9804 - val_loss: 1.7847 - val_acc: 0.8599
Epoch 25/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1639 - acc: 0.9816Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1646 - acc: 0.9814 - val_loss: 1.7761 - val_acc: 0.8647
Epoch 26/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1721 - acc: 0.9811Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1769 - acc: 0.9808 - val_loss: 1.7718 - val_acc: 0.8599
Epoch 27/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1759 - acc: 0.9812Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1728 - acc: 0.9816 - val_loss: 1.8532 - val_acc: 0.8563
Epoch 28/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1341 - acc: 0.9819Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1341 - acc: 0.9820 - val_loss: 1.7629 - val_acc: 0.8515
Epoch 29/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1458 - acc: 0.9840Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1515 - acc: 0.9835 - val_loss: 1.8086 - val_acc: 0.8503
Epoch 30/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1849 - acc: 0.9805Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1827 - acc: 0.9804 - val_loss: 1.8602 - val_acc: 0.8503
Epoch 31/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1627 - acc: 0.9829Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 515us/step - loss: 0.1598 - acc: 0.9832 - val_loss: 1.7952 - val_acc: 0.8527
Epoch 32/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1669 - acc: 0.9816Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1697 - acc: 0.9814 - val_loss: 1.8364 - val_acc: 0.8527
Epoch 33/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1380 - acc: 0.9838Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1403 - acc: 0.9838 - val_loss: 1.8874 - val_acc: 0.8539
Epoch 34/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1687 - acc: 0.9802Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1659 - acc: 0.9802 - val_loss: 1.8252 - val_acc: 0.8527
Epoch 35/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1672 - acc: 0.9814Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1660 - acc: 0.9814 - val_loss: 1.8514 - val_acc: 0.8539
Epoch 36/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1519 - acc: 0.9835Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 493us/step - loss: 0.1519 - acc: 0.9832 - val_loss: 1.8333 - val_acc: 0.8527
Epoch 37/37
6560/6680 [============================>.] - ETA: 0s - loss: 0.1724 - acc: 0.9816Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1706 - acc: 0.9817 - val_loss: 1.6981 - val_acc: 0.8587

Batch size=41 Epoch=40
Train on 6680 samples, validate on 835 samples
Epoch 1/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1572 - acc: 0.9828Epoch 00001: val_loss improved from inf to 1.71220, saving model to saved_models2/weights.best.ResNet_bs41_ep40.hdf5
6680/6680 [==============================] - 3s 515us/step - loss: 0.1558 - acc: 0.9826 - val_loss: 1.7122 - val_acc: 0.8647
Epoch 2/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1703 - acc: 0.9806Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1681 - acc: 0.9808 - val_loss: 1.7373 - val_acc: 0.8587
Epoch 3/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1655 - acc: 0.9817Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1627 - acc: 0.9820 - val_loss: 1.7543 - val_acc: 0.8683
Epoch 4/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1816 - acc: 0.9799Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1784 - acc: 0.9802 - val_loss: 1.7645 - val_acc: 0.8635
Epoch 5/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1585 - acc: 0.9823Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1605 - acc: 0.9823 - val_loss: 1.7530 - val_acc: 0.8635
Epoch 6/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1842 - acc: 0.9803Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1870 - acc: 0.9801 - val_loss: 1.7614 - val_acc: 0.8635
Epoch 7/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1783 - acc: 0.9806Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1775 - acc: 0.9808 - val_loss: 1.7600 - val_acc: 0.8707
Epoch 8/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1530 - acc: 0.9828Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1503 - acc: 0.9831 - val_loss: 1.7361 - val_acc: 0.8635
Epoch 9/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1895 - acc: 0.9790Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1861 - acc: 0.9793 - val_loss: 1.8424 - val_acc: 0.8539
Epoch 10/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1880 - acc: 0.9791Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1911 - acc: 0.9786 - val_loss: 1.7495 - val_acc: 0.8551
Epoch 11/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1870 - acc: 0.9805Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1922 - acc: 0.9802 - val_loss: 1.7781 - val_acc: 0.8623
Epoch 12/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1577 - acc: 0.9829Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1585 - acc: 0.9828 - val_loss: 1.7773 - val_acc: 0.8575
Epoch 13/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1487 - acc: 0.9831Epoch 00013: val_loss improved from 1.71220 to 1.63771, saving model to saved_models2/weights.best.ResNet_bs41_ep40.hdf5
6680/6680 [==============================] - 3s 521us/step - loss: 0.1492 - acc: 0.9829 - val_loss: 1.6377 - val_acc: 0.8647
Epoch 14/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1672 - acc: 0.9812Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1682 - acc: 0.9811 - val_loss: 1.7317 - val_acc: 0.8599
Epoch 15/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1600 - acc: 0.9826Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1572 - acc: 0.9829 - val_loss: 1.7548 - val_acc: 0.8611
Epoch 16/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1341 - acc: 0.9845Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 513us/step - loss: 0.1337 - acc: 0.9844 - val_loss: 1.8233 - val_acc: 0.8551
Epoch 17/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1643 - acc: 0.9837Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 514us/step - loss: 0.1664 - acc: 0.9835 - val_loss: 1.7456 - val_acc: 0.8587
Epoch 18/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1616 - acc: 0.9829Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 494us/step - loss: 0.1660 - acc: 0.9825 - val_loss: 1.7727 - val_acc: 0.8551
Epoch 19/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1520 - acc: 0.9825Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1523 - acc: 0.9823 - val_loss: 1.8884 - val_acc: 0.8539
Epoch 20/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1572 - acc: 0.9817Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1545 - acc: 0.9820 - val_loss: 1.8920 - val_acc: 0.8575
Epoch 21/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1501 - acc: 0.9820Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1565 - acc: 0.9816 - val_loss: 1.9248 - val_acc: 0.8527
Epoch 22/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1529 - acc: 0.9837Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 495us/step - loss: 0.1525 - acc: 0.9838 - val_loss: 1.8117 - val_acc: 0.8587
Epoch 23/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1754 - acc: 0.9820Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1776 - acc: 0.9819 - val_loss: 1.8790 - val_acc: 0.8575
Epoch 24/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1705 - acc: 0.9817Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1754 - acc: 0.9813 - val_loss: 1.8030 - val_acc: 0.8623
Epoch 25/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1633 - acc: 0.9814Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1673 - acc: 0.9811 - val_loss: 1.8461 - val_acc: 0.8527
Epoch 26/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1456 - acc: 0.9841Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1475 - acc: 0.9838 - val_loss: 1.8279 - val_acc: 0.8503
Epoch 27/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1495 - acc: 0.9838Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1505 - acc: 0.9838 - val_loss: 1.7921 - val_acc: 0.8551
Epoch 28/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1278 - acc: 0.9860Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1256 - acc: 0.9862 - val_loss: 1.8407 - val_acc: 0.8551
Epoch 29/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1630 - acc: 0.9834Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1610 - acc: 0.9835 - val_loss: 1.8389 - val_acc: 0.8623
Epoch 30/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.9817Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1722 - acc: 0.9813 - val_loss: 1.9057 - val_acc: 0.8515
Epoch 31/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1500 - acc: 0.9834Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1485 - acc: 0.9835 - val_loss: 1.7574 - val_acc: 0.8683
Epoch 32/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1509 - acc: 0.9832Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1545 - acc: 0.9831 - val_loss: 1.7156 - val_acc: 0.8695
Epoch 33/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1448 - acc: 0.9857Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1466 - acc: 0.9855 - val_loss: 1.8730 - val_acc: 0.8551
Epoch 34/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1649 - acc: 0.9812Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 515us/step - loss: 0.1641 - acc: 0.9813 - val_loss: 1.8926 - val_acc: 0.8491
Epoch 35/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1671 - acc: 0.9817Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 494us/step - loss: 0.1673 - acc: 0.9816 - val_loss: 1.9162 - val_acc: 0.8503
Epoch 36/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1737 - acc: 0.9803Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1781 - acc: 0.9799 - val_loss: 1.8548 - val_acc: 0.8515
Epoch 37/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1588 - acc: 0.9826Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1586 - acc: 0.9826 - val_loss: 1.8833 - val_acc: 0.8443
Epoch 38/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1326 - acc: 0.9835Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1302 - acc: 0.9838 - val_loss: 1.8256 - val_acc: 0.8491
Epoch 39/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1366 - acc: 0.9841Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1389 - acc: 0.9841 - val_loss: 1.8739 - val_acc: 0.8575
Epoch 40/40
6560/6680 [============================>.] - ETA: 0s - loss: 0.1383 - acc: 0.9846Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1382 - acc: 0.9846 - val_loss: 1.8535 - val_acc: 0.8587

Batch size=41 Epoch=50
Train on 6680 samples, validate on 835 samples
Epoch 1/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1903 - acc: 0.9791Epoch 00001: val_loss improved from inf to 1.65370, saving model to saved_models2/weights.best.ResNet_bs41_ep50.hdf5
6680/6680 [==============================] - 3s 505us/step - loss: 0.1908 - acc: 0.9790 - val_loss: 1.6537 - val_acc: 0.8683
Epoch 2/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1607 - acc: 0.9817Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1598 - acc: 0.9817 - val_loss: 1.7019 - val_acc: 0.8563
Epoch 3/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1320 - acc: 0.9848Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1328 - acc: 0.9846 - val_loss: 1.7150 - val_acc: 0.8587
Epoch 4/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1677 - acc: 0.9809Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1709 - acc: 0.9807 - val_loss: 1.7345 - val_acc: 0.8539
Epoch 5/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1556 - acc: 0.9816Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1533 - acc: 0.9817 - val_loss: 1.8734 - val_acc: 0.8515
Epoch 6/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1659 - acc: 0.9809Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1652 - acc: 0.9808 - val_loss: 1.7937 - val_acc: 0.8551
Epoch 7/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1950 - acc: 0.9791Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1917 - acc: 0.9793 - val_loss: 1.8296 - val_acc: 0.8587
Epoch 8/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1591 - acc: 0.9816Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1562 - acc: 0.9819 - val_loss: 1.8401 - val_acc: 0.8563
Epoch 9/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1598 - acc: 0.9838Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1607 - acc: 0.9835 - val_loss: 1.7646 - val_acc: 0.8575
Epoch 10/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1690 - acc: 0.9817Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1664 - acc: 0.9819 - val_loss: 1.7884 - val_acc: 0.8563
Epoch 11/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1414 - acc: 0.9857Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1404 - acc: 0.9858 - val_loss: 1.7427 - val_acc: 0.8527
Epoch 12/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1484 - acc: 0.9825Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1475 - acc: 0.9826 - val_loss: 1.7631 - val_acc: 0.8503
Epoch 13/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1588 - acc: 0.9822Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 493us/step - loss: 0.1571 - acc: 0.9823 - val_loss: 1.8621 - val_acc: 0.8527
Epoch 14/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1461 - acc: 0.9832Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1509 - acc: 0.9829 - val_loss: 1.7965 - val_acc: 0.8623
Epoch 15/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1521 - acc: 0.9840Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1554 - acc: 0.9838 - val_loss: 1.7679 - val_acc: 0.8551
Epoch 16/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1715 - acc: 0.9803Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1689 - acc: 0.9805 - val_loss: 1.8780 - val_acc: 0.8551
Epoch 17/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1612 - acc: 0.9832Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1583 - acc: 0.9835 - val_loss: 1.8182 - val_acc: 0.8707
Epoch 18/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1565 - acc: 0.9828Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1574 - acc: 0.9826 - val_loss: 1.8425 - val_acc: 0.8599
Epoch 19/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1692 - acc: 0.9823Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1682 - acc: 0.9823 - val_loss: 1.8540 - val_acc: 0.8551
Epoch 20/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1326 - acc: 0.9848Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1369 - acc: 0.9841 - val_loss: 1.8213 - val_acc: 0.8611
Epoch 21/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1646 - acc: 0.9823Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 516us/step - loss: 0.1620 - acc: 0.9825 - val_loss: 1.8165 - val_acc: 0.8647
Epoch 22/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1699 - acc: 0.9811Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1683 - acc: 0.9813 - val_loss: 1.8391 - val_acc: 0.8659
Epoch 23/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1571 - acc: 0.9834Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1543 - acc: 0.9837 - val_loss: 1.8831 - val_acc: 0.8623
Epoch 24/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1631 - acc: 0.9826Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1602 - acc: 0.9829 - val_loss: 1.8334 - val_acc: 0.8635
Epoch 25/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1573 - acc: 0.9848Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1579 - acc: 0.9847 - val_loss: 1.8277 - val_acc: 0.8611
Epoch 26/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1679 - acc: 0.9814Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1668 - acc: 0.9813 - val_loss: 1.7557 - val_acc: 0.8647
Epoch 27/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1713 - acc: 0.9831Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1708 - acc: 0.9831 - val_loss: 1.7893 - val_acc: 0.8635
Epoch 28/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1532 - acc: 0.9837Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1543 - acc: 0.9834 - val_loss: 1.9391 - val_acc: 0.8551
Epoch 29/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1858 - acc: 0.9800Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 517us/step - loss: 0.1867 - acc: 0.9801 - val_loss: 1.8824 - val_acc: 0.8599
Epoch 30/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1617 - acc: 0.9822Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1588 - acc: 0.9825 - val_loss: 1.8551 - val_acc: 0.8587
Epoch 31/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1503 - acc: 0.9837Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1476 - acc: 0.9840 - val_loss: 1.8314 - val_acc: 0.8587
Epoch 32/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1514 - acc: 0.9828Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1535 - acc: 0.9828 - val_loss: 1.8959 - val_acc: 0.8611
Epoch 33/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1462 - acc: 0.9834Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1510 - acc: 0.9831 - val_loss: 1.8666 - val_acc: 0.8659
Epoch 34/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1542 - acc: 0.9817Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1555 - acc: 0.9814 - val_loss: 1.8398 - val_acc: 0.8635
Epoch 35/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1530 - acc: 0.9845Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1530 - acc: 0.9844 - val_loss: 1.8540 - val_acc: 0.8551
Epoch 36/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1265 - acc: 0.9838Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1293 - acc: 0.9837 - val_loss: 1.8117 - val_acc: 0.8623
Epoch 37/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1372 - acc: 0.9841Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1348 - acc: 0.9844 - val_loss: 1.8175 - val_acc: 0.8563
Epoch 38/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1404 - acc: 0.9855Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1406 - acc: 0.9853 - val_loss: 1.7926 - val_acc: 0.8623
Epoch 39/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1431 - acc: 0.9852Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1430 - acc: 0.9853 - val_loss: 1.7772 - val_acc: 0.8575
Epoch 40/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1618 - acc: 0.9829Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1613 - acc: 0.9831 - val_loss: 1.7832 - val_acc: 0.8575
Epoch 41/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1686 - acc: 0.9811Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1724 - acc: 0.9810 - val_loss: 1.7558 - val_acc: 0.8599
Epoch 42/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1409 - acc: 0.9832Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1409 - acc: 0.9834 - val_loss: 1.9158 - val_acc: 0.8515
Epoch 43/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9819Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1591 - acc: 0.9817 - val_loss: 1.8460 - val_acc: 0.8503
Epoch 44/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1756 - acc: 0.9831Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1756 - acc: 0.9831 - val_loss: 1.7546 - val_acc: 0.8587
Epoch 45/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1336 - acc: 0.9860Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1312 - acc: 0.9862 - val_loss: 1.8531 - val_acc: 0.8551
Epoch 46/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1741 - acc: 0.9817Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 3s 512us/step - loss: 0.1728 - acc: 0.9819 - val_loss: 1.8555 - val_acc: 0.8623
Epoch 47/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1716 - acc: 0.9828Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1720 - acc: 0.9826 - val_loss: 1.8122 - val_acc: 0.8563
Epoch 48/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1510 - acc: 0.9840Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1483 - acc: 0.9843 - val_loss: 1.7970 - val_acc: 0.8551
Epoch 49/50
6560/6680 [============================>.] - ETA: 0s - loss: 0.1635 - acc: 0.9835Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1629 - acc: 0.9835 - val_loss: 1.8363 - val_acc: 0.8623
Epoch 50/50
6642/6680 [============================>.] - ETA: 0s - loss: 0.1562 - acc: 0.9842Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1562 - acc: 0.9841 - val_loss: 1.7905 - val_acc: 0.8551

Batch size=41 Epoch=55
Train on 6680 samples, validate on 835 samples
Epoch 1/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1486 - acc: 0.9829Epoch 00001: val_loss improved from inf to 1.72033, saving model to saved_models2/weights.best.ResNet_bs41_ep55.hdf5
6680/6680 [==============================] - 3s 510us/step - loss: 0.1582 - acc: 0.9822 - val_loss: 1.7203 - val_acc: 0.8575
Epoch 2/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1579 - acc: 0.9828Epoch 00002: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1571 - acc: 0.9829 - val_loss: 1.7714 - val_acc: 0.8563
Epoch 3/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1630 - acc: 0.9816Epoch 00003: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1624 - acc: 0.9817 - val_loss: 1.8058 - val_acc: 0.8575
Epoch 4/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9831Epoch 00004: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1557 - acc: 0.9831 - val_loss: 1.8205 - val_acc: 0.8563
Epoch 5/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1768 - acc: 0.9808Epoch 00005: val_loss did not improve
6680/6680 [==============================] - 3s 509us/step - loss: 0.1738 - acc: 0.9810 - val_loss: 1.8278 - val_acc: 0.8539
Epoch 6/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.9820Epoch 00006: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1650 - acc: 0.9822 - val_loss: 1.8254 - val_acc: 0.8575
Epoch 7/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1763 - acc: 0.9803Epoch 00007: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1754 - acc: 0.9804 - val_loss: 1.8145 - val_acc: 0.8515
Epoch 8/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1874 - acc: 0.9800Epoch 00008: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1864 - acc: 0.9802 - val_loss: 1.8545 - val_acc: 0.8563
Epoch 9/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1519 - acc: 0.9814Epoch 00009: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1544 - acc: 0.9813 - val_loss: 1.9141 - val_acc: 0.8503
Epoch 10/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1330 - acc: 0.9846Epoch 00010: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1359 - acc: 0.9844 - val_loss: 1.8302 - val_acc: 0.8563
Epoch 11/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1860 - acc: 0.9793Epoch 00011: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1854 - acc: 0.9793 - val_loss: 1.8056 - val_acc: 0.8515
Epoch 12/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1448 - acc: 0.9846Epoch 00012: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1426 - acc: 0.9847 - val_loss: 1.8080 - val_acc: 0.8563
Epoch 13/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1398 - acc: 0.9820Epoch 00013: val_loss did not improve
6680/6680 [==============================] - 3s 504us/step - loss: 0.1376 - acc: 0.9820 - val_loss: 1.8067 - val_acc: 0.8599
Epoch 14/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1483 - acc: 0.9848Epoch 00014: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1470 - acc: 0.9846 - val_loss: 1.8980 - val_acc: 0.8407
Epoch 15/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9826Epoch 00015: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1555 - acc: 0.9826 - val_loss: 1.8853 - val_acc: 0.8503
Epoch 16/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1601 - acc: 0.9831Epoch 00016: val_loss did not improve
6680/6680 [==============================] - 3s 501us/step - loss: 0.1632 - acc: 0.9826 - val_loss: 1.8587 - val_acc: 0.8551
Epoch 17/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1484 - acc: 0.9841Epoch 00017: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1459 - acc: 0.9844 - val_loss: 1.8354 - val_acc: 0.8551
Epoch 18/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1610 - acc: 0.9822Epoch 00018: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1618 - acc: 0.9822 - val_loss: 1.8707 - val_acc: 0.8599
Epoch 19/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1774 - acc: 0.9811Epoch 00019: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1770 - acc: 0.9811 - val_loss: 1.9307 - val_acc: 0.8527
Epoch 20/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1452 - acc: 0.9831Epoch 00020: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1426 - acc: 0.9834 - val_loss: 1.8316 - val_acc: 0.8563
Epoch 21/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1484 - acc: 0.9826Epoch 00021: val_loss did not improve
6680/6680 [==============================] - 3s 495us/step - loss: 0.1512 - acc: 0.9825 - val_loss: 1.9176 - val_acc: 0.8503
Epoch 22/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1700 - acc: 0.9797Epoch 00022: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1708 - acc: 0.9798 - val_loss: 1.8640 - val_acc: 0.8587
Epoch 23/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1740 - acc: 0.9812Epoch 00023: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1709 - acc: 0.9816 - val_loss: 1.8368 - val_acc: 0.8575
Epoch 24/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1580 - acc: 0.9841Epoch 00024: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1552 - acc: 0.9844 - val_loss: 1.8444 - val_acc: 0.8551
Epoch 25/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1554 - acc: 0.9828Epoch 00025: val_loss did not improve
6680/6680 [==============================] - 3s 507us/step - loss: 0.1551 - acc: 0.9829 - val_loss: 1.8432 - val_acc: 0.8539
Epoch 26/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1361 - acc: 0.9858Epoch 00026: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1418 - acc: 0.9855 - val_loss: 1.8263 - val_acc: 0.8575
Epoch 27/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1609 - acc: 0.9823Epoch 00027: val_loss did not improve
6680/6680 [==============================] - 3s 510us/step - loss: 0.1616 - acc: 0.9823 - val_loss: 1.8124 - val_acc: 0.8539
Epoch 28/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1587 - acc: 0.9828Epoch 00028: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1605 - acc: 0.9826 - val_loss: 1.8222 - val_acc: 0.8575
Epoch 29/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1758 - acc: 0.9814Epoch 00029: val_loss did not improve
6680/6680 [==============================] - 3s 511us/step - loss: 0.1777 - acc: 0.9810 - val_loss: 1.7615 - val_acc: 0.8551
Epoch 30/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1695 - acc: 0.9829Epoch 00030: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1709 - acc: 0.9825 - val_loss: 1.8649 - val_acc: 0.8575
Epoch 31/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1621 - acc: 0.9828Epoch 00031: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1634 - acc: 0.9828 - val_loss: 1.8051 - val_acc: 0.8635
Epoch 32/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1542 - acc: 0.9823Epoch 00032: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1539 - acc: 0.9825 - val_loss: 1.9162 - val_acc: 0.8527
Epoch 33/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1622 - acc: 0.9846Epoch 00033: val_loss did not improve
6680/6680 [==============================] - 3s 508us/step - loss: 0.1607 - acc: 0.9847 - val_loss: 1.8583 - val_acc: 0.8551
Epoch 34/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1976 - acc: 0.9787Epoch 00034: val_loss did not improve
6680/6680 [==============================] - 3s 495us/step - loss: 0.1993 - acc: 0.9784 - val_loss: 1.8949 - val_acc: 0.8563
Epoch 35/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1898 - acc: 0.9797Epoch 00035: val_loss did not improve
6680/6680 [==============================] - 3s 505us/step - loss: 0.1899 - acc: 0.9798 - val_loss: 1.7869 - val_acc: 0.8575
Epoch 36/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1701 - acc: 0.9823Epoch 00036: val_loss did not improve
6680/6680 [==============================] - 3s 494us/step - loss: 0.1732 - acc: 0.9822 - val_loss: 1.7569 - val_acc: 0.8635
Epoch 37/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1618 - acc: 0.9834Epoch 00037: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1609 - acc: 0.9832 - val_loss: 1.7923 - val_acc: 0.8587
Epoch 38/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1696 - acc: 0.9812Epoch 00038: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1698 - acc: 0.9811 - val_loss: 1.9269 - val_acc: 0.8515
Epoch 39/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1703 - acc: 0.9802Epoch 00039: val_loss did not improve
6680/6680 [==============================] - 3s 506us/step - loss: 0.1676 - acc: 0.9802 - val_loss: 1.8772 - val_acc: 0.8611
Epoch 40/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1548 - acc: 0.9828Epoch 00040: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1567 - acc: 0.9826 - val_loss: 1.8142 - val_acc: 0.8551
Epoch 41/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1666 - acc: 0.9825Epoch 00041: val_loss did not improve
6680/6680 [==============================] - 3s 498us/step - loss: 0.1661 - acc: 0.9826 - val_loss: 1.8720 - val_acc: 0.8551
Epoch 42/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1536 - acc: 0.9841Epoch 00042: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1541 - acc: 0.9841 - val_loss: 1.8437 - val_acc: 0.8587
Epoch 43/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1496 - acc: 0.9849Epoch 00043: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1500 - acc: 0.9847 - val_loss: 1.8672 - val_acc: 0.8527
Epoch 44/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1551 - acc: 0.9835Epoch 00044: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1542 - acc: 0.9834 - val_loss: 1.9599 - val_acc: 0.8539
Epoch 45/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1636 - acc: 0.9832Epoch 00045: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1631 - acc: 0.9834 - val_loss: 1.9295 - val_acc: 0.8551
Epoch 46/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1820 - acc: 0.9808Epoch 00046: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1811 - acc: 0.9810 - val_loss: 1.9263 - val_acc: 0.8515
Epoch 47/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1631 - acc: 0.9828Epoch 00047: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1603 - acc: 0.9829 - val_loss: 1.8972 - val_acc: 0.8503
Epoch 48/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1577 - acc: 0.9831Epoch 00048: val_loss did not improve
6680/6680 [==============================] - 3s 500us/step - loss: 0.1562 - acc: 0.9832 - val_loss: 1.8337 - val_acc: 0.8659
Epoch 49/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1695 - acc: 0.9822Epoch 00049: val_loss did not improve
6680/6680 [==============================] - 3s 497us/step - loss: 0.1694 - acc: 0.9822 - val_loss: 1.9263 - val_acc: 0.8575
Epoch 50/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1698 - acc: 0.9832Epoch 00050: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1669 - acc: 0.9835 - val_loss: 1.9187 - val_acc: 0.8515
Epoch 51/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1561 - acc: 0.9831Epoch 00051: val_loss did not improve
6680/6680 [==============================] - 3s 502us/step - loss: 0.1594 - acc: 0.9829 - val_loss: 1.9099 - val_acc: 0.8587
Epoch 52/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1482 - acc: 0.9837Epoch 00052: val_loss did not improve
6680/6680 [==============================] - 3s 499us/step - loss: 0.1470 - acc: 0.9837 - val_loss: 2.0299 - val_acc: 0.8479
Epoch 53/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1448 - acc: 0.9837Epoch 00053: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1436 - acc: 0.9838 - val_loss: 1.9781 - val_acc: 0.8491
Epoch 54/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1288 - acc: 0.9852Epoch 00054: val_loss did not improve
6680/6680 [==============================] - 3s 503us/step - loss: 0.1274 - acc: 0.9853 - val_loss: 1.8549 - val_acc: 0.8599
Epoch 55/55
6560/6680 [============================>.] - ETA: 0s - loss: 0.1470 - acc: 0.9832Epoch 00055: val_loss did not improve
6680/6680 [==============================] - 3s 496us/step - loss: 0.1444 - acc: 0.9835 - val_loss: 1.7842 - val_acc: 0.8611
In [56]:
pd.DataFrame(fitingdict)
Out[56]:
Batch_Size Epochs Test_Accuracy
0 35 35 85.406699
1 35 37 85.287081
2 35 40 84.928230
3 35 50 85.645933
4 35 55 85.287081
5 36 35 84.330144
6 36 37 84.928230
7 36 40 84.808612
8 36 50 85.645933
9 36 55 85.885167
10 37 35 85.765550
11 37 37 85.287081
12 37 40 85.645933
13 37 50 85.645933
14 37 55 85.406699
15 40 35 85.287081
16 40 37 85.645933
17 40 40 86.363636
18 40 50 86.124402
19 40 55 85.765550
20 41 35 85.765550
21 41 37 85.765550
22 41 40 86.602871
23 41 50 86.842105
24 41 55 86.004785

(IMPLEMENTATION) Load the Model with the Best Validation Loss

In [57]:
#take largest testaccuracy's batch size and epochs
ind=fitingdict['Test_Accuracy'].index(max(fitingdict['Test_Accuracy']))
bs=fitingdict['Batch_Size'][ind]
ep=fitingdict['Epochs'][ind]

#LOAD the model with Best validation loss 
Xception_model.load_weights('saved_models2/weights.best.ResNet_bs'+str(bs)+'_ep'+str(ep)+'.hdf5')

(IMPLEMENTATION) Test the Model

Try out your model on the test dataset of dog images. Ensure that your test accuracy is greater than 60%.

In [30]:
### TODO: Calculate classification accuracy on the test dataset.
# get index of predicted dog breed for each image in test set
Xception_predictions = [np.argmax(Xception_model.predict(np.expand_dims(feature, axis=0))) for feature in test_Xception]
# report test accuracy
test_accuracy = 100*np.sum(np.array(Xception_predictions)==np.argmax(test_targets, axis=1))/len(Xception_predictions)
print('Test accuracy: %.4f%%' % test_accuracy)
Test accuracy: 86.8421%
In [59]:
test_Xception[0].shape
Out[59]:
(7, 7, 2048)
In [60]:
len(Xception_model.predict(np.expand_dims(test_Xception[0], axis=0))[0])
Out[60]:
133
In [61]:
len(np.array(Xception_predictions))
Out[61]:
836
In [62]:
len(np.argmax(test_targets, axis=1))
Out[62]:
836
In [63]:
dog_names[np.argmax(test_targets,axis=1)[1]]
Out[63]:
'Doberman_pinscher'

(IMPLEMENTATION) Predict Dog Breed with the Model

Write a function that takes an image path as input and returns the dog breed (Affenpinscher, Afghan_hound, etc) that is predicted by your model.

Similar to the analogous function in Step 5, your function should have three steps:

  1. Extract the bottleneck features corresponding to the chosen CNN model.
  2. Supply the bottleneck features as input to the model to return the predicted vector. Note that the argmax of this prediction vector gives the index of the predicted dog breed.
  3. Use the dog_names array defined in Step 0 of this notebook to return the corresponding breed.

The functions to extract the bottleneck features can be found in extract_bottleneck_features.py, and they have been imported in an earlier code cell. To obtain the bottleneck features corresponding to your chosen CNN architecture, you need to use the function

extract_{network}

where {network}, in the above filename, should be one of VGG19, Resnet50, InceptionV3, or Xception.

In [64]:
"""
from keras.applications.resnet50 import ResNet50

# define ResNet50 model
ResNet50_model = ResNet50(weights='imagenet')

def extract_Resnet50(tensor):
	from keras.applications.resnet50 import ResNet50, preprocess_input
	return ResNet50(weights='imagenet', include_top=False).predict(preprocess_input(tensor))
"""
"""
def Resnet50_predict_breed(img_path):
    # extract bottleneck features for Resnet50 Model
    img=preprocess_input(path_to_tensor(img_path))
    bottleneck_feature = ResNet50(weights='imagenet', include_top=False).predict(img) 
    
    # obtain predicted vector
    predicted_vector = ResNet_model.predict(bottleneck_feature)
    
    # return dog breed that is predicted by the model
    return dog_names[np.argmax(predicted_vector)]

"""
Out[64]:
"\ndef Resnet50_predict_breed(img_path):\n    # extract bottleneck features for Resnet50 Model\n    img=preprocess_input(path_to_tensor(img_path))\n    bottleneck_feature = ResNet50(weights='imagenet', include_top=False).predict(img) \n    \n    # obtain predicted vector\n    predicted_vector = ResNet_model.predict(bottleneck_feature)\n    \n    # return dog breed that is predicted by the model\n    return dog_names[np.argmax(predicted_vector)]\n\n"
In [31]:
### TODO: Write a function that takes a path to an image as input
### and returns the dog breed that is predicted by the model.
from extract_bottleneck_features import *
def Xception_predict_breed(img_path):
    # extract bottleneck features for Resnet50 Model
    bottleneck_feature = extract_Xception(path_to_tensor(img_path)) 
    
    # obtain predicted vector
    predicted_vector = Xception_model.predict(bottleneck_feature)
    
    # return dog breed that is predicted by the model
    return dog_names[np.argmax(predicted_vector)]

Step 6: Write your Algorithm

Write an algorithm that accepts a file path to an image and first determines whether the image contains a human, dog, or neither. Then,

  • if a dog is detected in the image, return the predicted breed.
  • if a human is detected in the image, return the resembling dog breed.
  • if neither is detected in the image, provide output that indicates an error.

You are welcome to write your own functions for detecting humans and dogs in images, but feel free to use the face_detector and dog_detector functions developed above. You are required to use your CNN from Step 5 to predict dog breed.

Some sample output for our algorithm is provided below, but feel free to design your own user experience!

Sample Human Output

(IMPLEMENTATION) Write your Algorithm

In [32]:
### TODO: Write your algorithm.
### Feel free to use as many code cells as needed.
from keras.preprocessing import image                  
from os import walk
from os import listdir
from os.path import isfile, join
import random
import numpy as np
import cv2


def show_image(path):
    img = image.load_img(path, target_size=(224, 224))
    img = image.img_to_array(img)
    plt.imshow(img/255)
    plt.show()
    

def whos_face_is_this(img_path):
    if(dog_detector(img_path)):
        print("\n**************************************")
        show_image(img_path)
        print("hello, Doggy!")
        print("Your predicted breed is....")
        print(Xception_predict_breed(img_path))
        
    elif(humanface_detector(img_path)):
        print("\n**************************************")
        show_image(img_path)
        print("Hello, Human!")
        print("You look like a.... ")
        print(Xception_predict_breed(img_path))
        
    else:
        print("\n**************************************")
        show_image(img_path)
        print("**No face detected..ERROR..**")

Step 7: Test Your Algorithm

In this section, you will take your new algorithm for a spin! What kind of dog does the algorithm think that you look like? If you have a dog, does it predict your dog's breed accurately? If you have a cat, does it mistakenly think that your cat is a dog?

(IMPLEMENTATION) Test Your Algorithm on Sample Images!

Test your algorithm at least six images on your computer. Feel free to use any images you like. Use at least two human and two dog images.

Question 6: Is the output better than you expected :) ? Or worse :( ? Provide at least three possible points of improvement for your algorithm.

Answer:

In [40]:
## TODO: Execute your algorithm from Step 6 on
## at least 6 images on your computer.
## Feel free to use as many code cells as needed.

#load test files from dog-project/dog_images
doggy = np.array(glob("dog_images/*"))

print('No. of files:', len(doggy))
No. of files: 12
In [41]:
for d in doggy:
    whos_face_is_this(d)
**************************************
hello, Doggy!
Your predicted breed is....
Chesapeake_bay_retriever

**************************************
hello, Doggy!
Your predicted breed is....
Pembroke_welsh_corgi

**************************************
hello, Doggy!
Your predicted breed is....
Labrador_retriever

**************************************
hello, Doggy!
Your predicted breed is....
Golden_retriever

**************************************
hello, Doggy!
Your predicted breed is....
Alaskan_malamute

**************************************
hello, Doggy!
Your predicted breed is....
Dalmatian

**************************************
hello, Doggy!
Your predicted breed is....
American_water_spaniel

**************************************
hello, Doggy!
Your predicted breed is....
Dalmatian

**************************************
hello, Doggy!
Your predicted breed is....
Collie

**************************************
hello, Doggy!
Your predicted breed is....
Irish_water_spaniel

**************************************
hello, Doggy!
Your predicted breed is....
Golden_retriever

**************************************
hello, Doggy!
Your predicted breed is....
Icelandic_sheepdog
In [42]:
#load test files from dog-project/Hooman_images
hooman = np.array(glob("Hooman_images/*"))

print('No. of files:', len(hooman))
No. of files: 8
In [43]:
for h in hooman:
    whos_face_is_this(h)
**************************************
Hello, Human!
You look like a.... 
Chinese_crested

**************************************
**No face detected..ERROR..**

**************************************
**No face detected..ERROR..**

**************************************
hello, Doggy!
Your predicted breed is....
Alaskan_malamute

**************************************
Hello, Human!
You look like a.... 
Poodle

**************************************
Hello, Human!
You look like a.... 
Belgian_tervuren

**************************************
**No face detected..ERROR..**

**************************************
hello, Doggy!
Your predicted breed is....
Alaskan_malamute
In [65]:
#load test files from dog-project/My_Pic
Mypic = np.array(glob("My_Pic/*"))
print('No. of files:', len(Mypic))
No. of files: 2
In [66]:
for my in Mypic:
    whos_face_is_this(my)
**************************************
Hello, Human!
You look like a.... 
Bichon_frise

**************************************
Hello, Human!
You look like a.... 
Bichon_frise

Question 6. Is the output better than you expected:) ? Or worse :( ? Provide at least three possible points of improvement for your algorithm.

Answer:

Yes, my output is better than i expected as we can see that-

  • (American_water_spaniel and Irish_water_spaniel) , (Icelandic_sheepdog,Pembroke_welsh_corgi) looks similar in skin colour but they are predicted 100% correctly, same we can see that retriever dogs like Chesapeake_bay_retriever,Labrador_retriever and Golden_retriever are predicted perfectly .

  • This model predict dog label correctly in group of same dogs(look Chesapeake_bay_retriever).

  • This model predict dog label for a dog correcty in human with dog image(look Alaskan_malamute with human).

  • This model predict human label for fake dog(camera filter image)- and gave the most resemble label to it as we can Chinese_crested dog has long hairstyles like that girl in pic.

  • This model correctly shows error when no face resembleing with human or dog is detected (look cat and tiger).

  • This model correctly put same label on my two pics.

Provide at least three possible points of improvement for your algorithm.

  • Earlier as we used harrclassifier for human face detection there we can use one of Bottleneck Features model we used in dog detector to detect human image.

  • As we can see 2nd last image of girl that was rotated was not identified by algo due to rotation varience hence Image augumentation is needed here to improve accuracy.

  • This can also be improved if algo can identify correctly more than one dog breed in group of different dogs(above 7th img from starting ,there it only identify Collie dog breed and not the other one).

Please download your notebook to submit

In order to submit, please do the following:

  1. Download an HTML version of the notebook to your computer using 'File: Download as...'
  2. Click on the orange Jupyter circle on the top left of the workspace.
  3. Navigate into the dog-project folder to ensure that you are using the provided dog_images, lfw, and bottleneck_features folders; this means that those folders will not appear in the dog-project folder. If they do appear because you downloaded them, delete them.
  4. While in the dog-project folder, upload the HTML version of this notebook you just downloaded. The upload button is on the top right.
  5. Navigate back to the home folder by clicking on the two dots next to the folder icon, and then open up a terminal under the 'new' tab on the top right
  6. Zip the dog-project folder with the following command in the terminal: zip -r dog-project.zip dog-project
  7. Download the zip file by clicking on the square next to it and selecting 'download'. This will be the zip file you turn in on the next node after this workspace!
In [48]:
!!jupyter nbconvert *.ipynb
Out[48]:
['[NbConvertApp] Converting notebook dog_app.ipynb to html',
 '[NbConvertApp] Writing 4686258 bytes to dog_app.html']